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Tailoring compositional and microstructural complexity in nanostructured alloys

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Tailoring compositional and microstructural complexity in nanostructured alloys

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Content Copyright 2023 Daniel C. Goodelman
Tailoring compositional and microstructural complexity in
nanostructured metallic alloys

by

Daniel C. Goodelman

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirement for the Degree
DOCTOR OF PHILOSOPHY
(MECHANICAL ENGINEERING)

August 2023

ii

Acknowledgements
This dissertation is dedicated to my grandmother Silvia and my great aunts Linda and Gloria.

First, I would like to thank my advisor, Professor Andrea Hodge. Out of all the PI’s I had contacted
during my graduate school application process, Professor Hodge was the only one who (1) took
the time to chat with me and (2) saw my potential as a scientific researcher; she was the only PI to
take a chance on me and accept me into a PhD program (on fellowship at that!). Through the years,
she constantly pushed me to become better at the craft and helped mold me into the scientist I am
today. For these reasons I am forever grateful to her.

The studies across this dissertation could not have been accomplished without the assistance of
my distinguished collaborators, Professor Diana Farkas at Virginia Tech, Professor Paulo Branicio
at USC, his student Aoyan Liang, and Professor Michael Kassner at USC. I would like to thank
Professor Horst Hahn and Dr. Miriam Botros for hosting me during my visits to Karlsruhe Institute
of Technology. Special thanks to Professor Leonardo Velasco Estrada at the National University
of Colombia, Dr. Megan Cordill at the Erich Schmid Institute, and Dr. Tim Rupert at University
of California – Irvine for helpful discussions. Thank you to Dr. Yunbin Guan at CalTech for his
operation of the NanoSIMS and for his hospitality. Thank you to my thesis defense committee
members, Professor Paulo Branicio, Professor Mitul Luhar, Professor Michael Kassner, and
Professor Yu-Tsun Shao.

I would like to acknowledge the funding from the Office of Naval Research [Award N00014-22-
1-2712] and the National Science Foundation [Grant DMR-1709771] for making this research
possible.

I want to thank my colleagues at the Core Center for Excellence in Nano Imaging, particularly Dr.
Amir Avishai. Amir began as a staff scientist shortly after my RAship at the center started and
took me under his wing to enhance my understanding of electron microscopy. When I started at
the center, I only had a very trivial idea of how the instruments worked; Amir ensured that that
would no longer be the case. His commitment to developing excellent, knowledgeable researchers
is unmatched.

My time at USC was all the better thanks to the friends I developed through the years. Thank you
to my colleagues in the Hodge Group, Adie Alwen, Kyle Russell, Danielle White, Karina
Hemmendinger, Ikponmwosa Iyinbor, and Andre Bohn, as well as honorary member TJ Oros, for
not only your wealth of knowledge but for making me feel welcome. No better support group
exists in academia. I especially want to thank my Hodge Group predecessors Dr. Chelsea Appleget,
Dr. Joel Bahena, and Dr. Alina Garcia-Taormina, for being excellent mentors and even better
friends. This PhD would not be possible without contributions from each of you.

I want to thank my family for all their love and support. My parents, Mark and Joanne, have never
thought twice about my career choices and have constantly encouraged me to become the most
accomplished version of myself. Thank you to my sister Katie for always being herself and to my
cousin Craig for being the older sibling I never had. Special thanks to Sado and Servete Dollaku
iii

for being my west coast parental guardians and for treating me like their own son. Even more
special thanks to Atlas Dollaku for being the bestest puppy.

Lastly, I want to thank my partner Esma Dollaku. Es and I met at my lowest point in the PhD
where I did not think I had the chops to finish. Her unwavering love and support over the years
helped propel me out of those doldrums and made the difficulties of being a graduate student much
more tolerable. This dissertation is as much a testament to her character as it is to my research
efforts; it would not have been accomplished without her.

iv

Table of Contents
Acknowledgements ....................................................................................................................... ii
List of Tables .............................................................................................................................. viii
List of Figures ............................................................................................................................... ix
Abstract ....................................................................................................................................... xiv

1. Chapter 1: Introduction ........................................................................................................ 1

2. Chapter 2: Background......................................................................................................... 3
2.1. Nanostructured Materials ..................................................................................................... 3
2.2. Synthesis Techniques ........................................................................................................... 4
2.2.1. Magnetron Sputtering ....................................................................................................... 5
2.2.1.1. Nanostructured alloys synthesized via magnetron sputtering ...................................... 7
2.3. Films with compositional complexity: multi-principal element alloys (MPEAs) ............... 9
2.3.1. The sluggish diffusion effect .......................................................................................... 11
2.3.2. The severe lattice distortion effect ................................................................................. 12
2.3.3. “Cocktail effects”: The interaction of alloying elements ............................................... 13
2.3.4. The high entropy effect .................................................................................................. 14
2.3.5. Compositionally complex alloys (CCAs) ...................................................................... 16
2.4. Film Microstructural Space................................................................................................ 18
2.4.1. Microstructures of films ................................................................................................. 18
2.4.2. Microstructural complexity ............................................................................................ 21
2.4.2.1. Nanotwinned (NT) Materials ...................................................................................... 22
2.4.2.2. Heterogeneous Nanostructured Materials (HNMs) .................................................... 26
2.4.2.2.1. Residual Stresses and stored energy gradients ........................................................... 29
2.5. Summary ............................................................................................................................ 31

v

3. Chapter 3: Experimental Methods .................................................................................... 33
3.1. Magnetron Sputtering ........................................................................................................ 33
3.2. Residual stresses and profilometry .................................................................................... 35
3.3. Heat Treatments ................................................................................................................. 37
3.4. Microstructural Characterization ....................................................................................... 40
3.4.1. X-ray Diffraction ............................................................................................................ 40
3.4.2. Scanning Electron Microscopy and Energy-Dispersive X-ray Spectroscopy ................ 41
3.4.3. Electron Back Scatter Diffraction and Transmission Kikuchi Diffraction .................... 43
3.4.4. Focused Ion Beam .......................................................................................................... 45
3.4.5. Transmission Electron Microscopy ................................................................................ 47
3.4.6. Scanning Transmission Electron Microscopy ................................................................ 48
3.4.7. Secondary Ion Mass Spectrometry (SIMS) and NanoSIMS .......................................... 49
3.5. Mechanical Characterization ............................................................................................. 50
3.5.1. Vickers micro-indentation .............................................................................................. 50
3.5.2. Nanoindentation ............................................................................................................. 53

4. Chapter 4: Phase transition zones in compositionally complex alloys ........................... 55
4.1. Introduction ........................................................................................................................ 55
4.2. Materials & methods .......................................................................................................... 57
4.3. Results & discussion .......................................................................................................... 59
4.3.1. AlCrFeNiTi – the role of multiple “large” elements ..................................................... 60
4.3.2. AlCoFeNiTi – the role of multiple “large” elements influenced by “small” element
substitution .................................................................................................................................... 66
4.3.3. Nanoindentation ............................................................................................................. 72
4.4. Conclusions ........................................................................................................................ 74

5. Chapter 5: Influence of microstructural distribution in heterogeneous
nanomaterials .............................................................................................................................. 75
5.1. Introduction ........................................................................................................................ 75
vi

5.2. Experimental Methods ....................................................................................................... 77
5.3. Results and Discussion ...................................................................................................... 79
5.3.1. As-sputtered Microstructure .......................................................................................... 79
5.3.2. Heterogeneous Nanodomain Formation ........................................................................ 83
5.3.2.1. Region I – Substrate Interface .................................................................................... 86
5.3.2.2. Region II – Middle Section ......................................................................................... 87
5.3.2.3. Region III – Free Surface ........................................................................................... 88
5.3.3. Graphical Nanodomain Distribution ............................................................................. 89
5.3.4. Deformation Behavior due to Nanodomain Distribution ............................................... 90
5.4. Conclusions ........................................................................................................................ 96

6. Chapter 6: A surrogate screening method for the development of tailored additively
manufactured microstructures .................................................................................................. 97
6.1. Introduction ........................................................................................................................ 97
6.2. Materials and Methods ....................................................................................................... 99
6.3. Results and Discussion .................................................................................................... 101
6.3.1. As sputtered microstructures ........................................................................................ 101
6.3.2. Inconel microstructures without additions ................................................................... 104
6.3.2.1. Comparison to AM Inconel 718 microstructures from literature ............................. 110
6.3.3. Effect of novel elemental additions in Inconel microstructures ................................... 111
6.4. Conclusions ...................................................................................................................... 116

7. Chapter 7: General Conclusions and Future Research Outlook .................................. 118

References .................................................................................................................................. 122
Appendix A. Summary of sputtered samples ......................................................................... 158
Appendix B. Supplementary Materials for Chapter 4 .......................................................... 181
vii

Appendix C. Supplementary Materials for Chapter 5 .......................................................... 183
Appendix D. Supplementary Materials for Chapter 6 .......................................................... 184

viii

List of Tables
Table 1: Comparison of standard composition ranges for Inconel 718 and 725, provided in
wt.% [161, 162], where “Bal*” refers to balance. ........................................................................ 28
Table 2. Crystallinity and average crystallite size of samples in all systems. .............................. 59
Table 3: Elemental composition derived from EDS data for systems 1 and 2 in the
AlCrFeNiTi family........................................................................................................................ 60
Table 4: Elemental composition derived from EDS data for systems 3 and 4 in the
AlCoFeNiTi family. ...................................................................................................................... 67
Table 5: Reduced modulus and hardness values determined via nanoindentation. Samples are
notated based on their respective crystallography, where “●” indicates an amorphous
structure, “◊” indicates a mixed structure, and “□” indicates a crystalline structure. ................... 73
Table 6: top surface compositional data for as-sputtered (AS) and heat-treated (HT) samples in
wt %. Composition ranges for standard Inconel is provided for reference. ................................. 78
Table 7: Mechanical properties via indentation for all samples from this study compared to
literature values* [311]. **Indentation hardness for solution annealed and age-hardened
determined from Rockwell hardness in literature. ........................................................................ 92
Table 8: Composition of samples in at. % (wt. %). Composition ranges for standard Inconel
718 is provided for reference [162]. ........................................................................................... 104
Table 9: As deposited residual stress for all samples. ................................................................ 107
Table 10: AlFeNiTi sputtered samples – Sputtered at KIT ........................................................ 158
Table 11: AlCrFeNiTi sputtered samples ................................................................................... 159
Table 12: AlCoFeNiTi sputtered samples................................................................................... 164
Table 13: CoFeNiTi sputtered samples for collaboration with Diana Farkas, Paulo Branicio,
and Aoyan Liang ......................................................................................................................... 165
Table 14: CrFeNiTi sputtered samples for collaboration with Diana Farkas, Paulo Branicio,
and Aoyan Liang ......................................................................................................................... 165
Table 15: Inconel 725 sputtered samples .................................................................................... 167
Table 16: Inconel 718 sputtered samples .................................................................................... 179
Table 17: Sputtering conditions used for each sample run within the AlCrFeNiTi system.
Within varied Al samples, Al power was increased while power provided to other targets was
kept constant. Likewise for the varied Ti samples. ..................................................................... 181
Table 18: Sputtering conditions used for each sample run within the AlCoFeNiTi system.
Within varied Al samples, Al power was increased while power provided to other targets was
kept constant. Likewise for the varied Ti samples. ..................................................................... 181
Table 19: Deposition conditions of samples in Chapter 6 .......................................................... 184

ix

List of Figures
Figure 1: TEM micrographs of nanostructured Ni samples synthesized via (a) ball milling, (b)
electrodeposition, and (c) sputtering [16]. ...................................................................................... 4
Figure 2: The Thornton diagram, describing microstructural formation in magnetron sputtered
films as influenced by argon pressure and substrate temperature. Based on the figure, there are
four distinct zones with variations in film growth structure: zones 1 and 2 (columnar grain
growth), zone 3 (equiaxed grain growth), and zone T (transition between columnar and
equiaxed growth) [21]. .................................................................................................................... 6
Figure 3: Schematic of co-sputtering configuration of a binary alloy [53]. ................................... 8
Figure 4: Ashby diagram comparing fracture toughness and yield strength for a variety of
materials. MPEAs are notated in orange [79]. .............................................................................. 10
Figure 5: The effect of atom size difference on atom positions in (a) a dilute solution and (b)
an MPEA solution. The variability in atom positions in (b) contribute to an excess
configurational entropy [81]. ........................................................................................................ 11
Figure 6: Correlation between the root mean square residual strain εRMS (theoretical model)
and atomic size difference δ (empirical model) for a variety of metallic glass forming alloys
[105]. ............................................................................................................................................. 13
Figure 7: Hardness as a function of Al content in the AlxCoCrCuFeNi MPEA system [94]. ...... 14
Figure 8: Plot of entropy of mixing v. number of alloying elements. Zones for low, medium,
and high entropy alloys are indicated [107]. ................................................................................. 15
Figure 9: (a) flexural strength-fracture strain of CrNbTaVW and CrNbTaVW1.7 samples at 298
K, 673 K and 873 K [118]. (b) UTS versus tensile εf at room temperature of heat-treated alloys
in a state close to equilibrium. Al7Co23Cr23Fe23Ni23 alloy, hcp and fcc, alloys with
eutectic-like microstructures, L12 in fcc, single phase alloys [112]. ...................................... 17
Figure 10: Free energy diagram for nucleation, identifying a critical radius. ΔG is the total free
energy, ΔGs is the surface free energy, ΔGv is the bulk free energy, Gcrit is the critical free
energy, and rc is the critical radius [124]. ..................................................................................... 19
Figure 11: Top view illustration of a thin film undergoing normal grain growth. Large grains
tend to grow larger and small grains shrink and disappear, such that average grain size
increases over time [126]. ............................................................................................................. 20
Figure 12: schematic of a (a) conventional grain boundary and (b) nanoscale twin boundary.
The red ┴ symbol denotes dislocation motion, “d” represents the grain size, and λ denotes twin
thickness [156]. ............................................................................................................................. 23
Figure 13: Cross-sectional bright field TEM comparing as-sputtered (A) Cu2Al-A (λ=5 nm),
(B) Cu2Al-B (λ=18 nm), (C) Cu10Ni-A (λ=13 nm), and (D) Cu10Ni-B (λ=31 nm); and (E)
representative XRD scans of the NT alloys. The arrow to the left indicates the film growth
[144]. ............................................................................................................................................. 25
Figure 14: Strength-ductility plot comparing heterogeneous nanostructured materials (GNGs)
to other conventional nanostructured materials, such as coarse-grained (CG) and nanograined
(NG) structures. We can see that GNGs exist in an otherwise unexplored space of strength-
ductility synergy within the material genome [154]. .................................................................... 27
x

Figure 15: Illustration of heterogeneous structural formation in NT Inconel 725 films at 3, 5,
and 8 hours of heat treatment. Depending on the length of the treatment, carbides, rafted
structures, δ-phase precipitates, and ALGs can form, due to an intrinsic stored energy gradient
[143]. ............................................................................................................................................. 29
Figure 16: Grain orientation spread (GOS) map and corresponding grain distribution plots,
highlighting a gradient in GOS [143]. .......................................................................................... 30
Figure 17: Schematic of sputtering chamber [200]....................................................................... 33
Figure 18: Schematic of co-sputtering arrangement, including the usage of three sources,
masking, and a shutter to produce multiple samples in a single sputtering run............................ 35
Figure 19: Profile data acquisition by a stylus-type profilometer [203]. ...................................... 37
Figure 20: Temperature v. time graph of Inconel 725 standard age hardening treatment. ........... 38
Figure 21: Temperature v. time graph of Inconel 725 age hardening treatment used in this
work. The initial solution anneal and end phase portions of the standard treatment were skipped.
....................................................................................................................................................... 39
Figure 22: Temperature v. time graph of Inconel 718 double aging heat treatment leveraged in
this work. The initial solution anneal was skipped, as sputtering forces a solid solution. ........... 40
Figure 23: Example XRD spectra of various CuAl and CuNi films synthesized using different
sputtering parameters [144]. ......................................................................................................... 41
Figure 24: Illustration of several signals generated by the electron beam–specimen interaction
in the scanning electron microscope and the regions from which the signals can be detected
[213]. ............................................................................................................................................. 42
Figure 25: Top surface EBSD IPF maps showing grain evolution of as-sputtered (A)
Cu2Al-A, (B) Cu2Al-B, (C) Cu10Ni-A, and (D) Cu10Ni-B after heat treatments performed at
200°C, 400°C, and 600°C. Dashed boxes highlight instances of significant grain growth, note
the changes in scale bar. The IPF triangle is shown to the right of the scans [144]. .................... 44
Figure 26: TKD results from the nanocrystalline Cu sample. The scale bar in all images is 500
nm. (a) DF image collected using forescatter detectors. (b) ODF image highlighting
orientation variations. (c) TKD pattern quality map of the same area. (d) TKD orientation map
(inverse pole figure z-direction coloring), with high-angle boundaries in black, low-angle
boundaries in grey and coincident site lattice boundaries in colors. White arrows mark
locations showing evidence of nanocrystalline grain growth [219]. ............................................ 45
Figure 27: The steps involved in FIB sectioning showing the preparation of the chosen area
(a), cutting the side trenches and preparing for lift-out (b), the micromanipulator is attached to
the sample for lift-out (c) and the sample is attached to a copper TEM grid (d) [222]. ............... 46
Figure 28: Illustration of TEM aperture and lens configuration for different modes: (a) bright
field, (b) dark field, and (c) SAED with corresponding image results of Hf-Ti multilayers (d-f)
[225]. ............................................................................................................................................. 48
Figure 29: (A) BF-STEM image of heterogenous precipitation and microstructural behavior in
magnetron sputtered Inconel 725 after 5 hours of heat treatment. SAED pattern provided inset
confirms the presence of δ precipitates. (B) EDS maps of Ni, Cr, Ti, and Nb highlighting
location of different precipitates where white scale bars are 1 µm. [143]. .................................. 49
xi

Figure 30: NanoSIMS maps of Inconel 625 showing how S segregates to Al2O3 sites, leading
to embrittlement [207]. ................................................................................................................. 50
Figure 31: (a) Representative SEM surface micrographs of Vickers indents and (b) FIB cross-
sectional micrographs underneath the indents in the Ag foils containing (1) 10%, (2) 40%, and
(3) 100% NT grains [230]. ............................................................................................................ 52
Figure 32: Representative nanoindentation load-displacement curve. ......................................... 54
Figure 33: Varied Al in AlCrFeNiTi family (System 1) - top surface SEM micrographs (a, b,
d, e, g, and h) and diffractograms (c, f, and i). Each row represents samples with the same Al
content (7, 15, and 33 at% respectively). Columns are split amongst samples that were in
either the “top” or “bottom” substrate quadrant position during the sputtering process, while
diffractograms are color-coded based on that position. ................................................................ 61
Figure 34: Varied Ti in AlCrFeNiTi family (system 2) - top surface SEM micrographs (a, b, d,
e, g, and h) and diffractograms (c, f, and i). Each row represents samples with the same Ti
content (5, 13, and 32 at% respectively). Columns are split amongst samples that were in
either the “top” or “bottom” substrate quadrant position during the sputtering process, while
diffractograms are color-coded based on that position. ................................................................ 63
Figure 35: Top surface SEM micrographs (a – f) and diffractograms (g) for refined samples
within system 2. Diffractogram patterns and SEM micrograph borders are color coded by
sample. Rows and diffractograms are split amongst samples with either “more” or “less” Al
content. Samples with “more” Al content have an Al composition greater than 23 at%,
whereas those with “less” Al content refer to samples with a higher proportion of Cr, Fe, and Ni
content in comparison to the Al content. Columns represent a specific Ti content (either 5, 7,
or 8 at%, respectively). ................................................................................................................. 65
Figure 36: Varied Al in AlCoFeNiTi family (system 3) - top surface SEM micrographs (a, b,
d, e, g, and h) and diffractograms (c, f, and i). Each row represents samples with the same Al
content (5 10, and 30 at% respectively). Columns are split amongst samples that were in either
the “top” or “bottom” substrate quadrant position during the sputtering process, while
diffractograms are color-coded based on that position. ................................................................ 69
Figure 37: Varied Ti in AlCoFeNiTi family (system 4) - Top surface SEM micrographs (a, b,
d, e, g, and h) and diffractograms (c, f, and i). Each row represents samples with the same Ti
content (5, 9, and 35 at% respectively. Columns are split amongst samples that were in either
the “top” or “bottom” substrate quadrant position during the sputtering process, while
diffractograms are color-coded based on that position. ................................................................ 70
Figure 38: Crystallography maps of samples in the AlCrFeNiTi (a) and AlCoFeNiTi (b)
families of CCAs. Samples are compared by their Al and Ti content and categorized by their
respective crystallography: dark blue data points indicate amorphous structures, light blue
indicates “mixed” structures, and yellow indicates crystalline structures. The red dotted lines
on the y-axes represent the Ti threshold at which amorphous phases begin to form. .................. 71
Figure 39: Calculated changes in residual stress as a function of radius of curvature based on
Stoney’s equation for an ~8µm thick Inconel 725 sample deposited on glass (orange) and Si
(blue) substrates. (a) Shows how a tensile residual stress is present for negative radii of
curvature while (b) shows a compressive residual stress for positive radii of curvature. ............ 80
xii

Figure 40: As-sputtered characterization of samples deposited on (red) corning eagle glass
and (green) Si <100> substrates, including (a, b) top surface SEM micrographs, (c, e) bright
field TEM micrographs with yellow arrow indicating growth direction, (d, f) grain width
distributions, and corresponding (g) XRD patterns. ..................................................................... 81
Figure 41: Dark field STEM micrographs of as-sputtered (a) fine NT and (b) coarse NT
sample. Misoriented growth region between substrate and columnar regions is indicated by
white dotted arrow. TKD patterns with pole figure provided for each micrograph, highlighting
misorientation in area close to substrate. Growth direction of both samples indicated by
orange arrow inset of (a). .............................................................................................................. 83
Figure 42: (a) DF STEM micrograph of gradient heterogeneous sample post-heat treatment.
Micrograph is divided into three Regions: I, II, and III, where feature size distributions are
provided in the insets. (b) Magnified micrographs of each region with annotations provided for
notable nanodomains (see legend). (c) TKD patterns and EDS maps of selected area of each
Region, highlighted in orange. Average feature sizes for each section included. IPFs provided
for orientations of identified phases in each TKD pattern. White bars on TKD patterns
indicate 500nm scale. .................................................................................................................... 85
Figure 43: (a) DF STEM micrograph of uniform heterogeneous sample post-heat treatment.
Micrograph is divided into three Regions: I, II, and III, where feature size distributions are
provided in the insets. (b) Magnified micrographs of each region with annotations provided for
notable nanodomains (see legend). (c) TKD patterns and EDS maps of selected area of each
Region, highlighted in orange. Average feature sizes for each section included. IPFs provided
for orientations of identified phases in each TKD pattern. White bars on TKD patterns
indicate 500nm scale. .................................................................................................................... 86
Figure 44: Schematic illustration of (a) NT heterogeneous nanostructured material (HNM), (b)
uniform HNM, and (c) gradient HNM. Abnormally large grains are indicated by the grey
shapes, delta phase by blue streaks, Cr-C by green spheres, rafted structured by striped, purple
pattern, annealing twins by gold lines, and nanocrystalline structures by grey octagonal
shapes. Growth direction is indicated by the black arrow to the left of (a). ................................. 90
Figure 45: SEM micrographs (a-d) and BF STEM micrographs (e-h) of Vickers indents for
fine-grained NT structure, coarse-grained NT structure, uniform HNM, and gradient HNM.
All Indents were performed using a 10 g load. ............................................................................. 93
Figure 46: (a) DF STEM micrograph of heterogeneous structure with uniform distribution of
nanodomains, highlighting regions of deformation near surface. Regions I (b) and II (c)
highlight deformation behavior of sample. (d) Corresponding EDS maps of entire deformed
region, highlighted by dotted gold box. ........................................................................................ 94
Figure 47: (a) DF STEM micrograph of heterogeneous structure with gradient distribution of
nanodomains, highlighting regions of deformation near surface, with shear bands indicated by
the dotted white lines. Regions I (b) and II (c) highlight deformation behavior of sample. (d)
Corresponding EDS maps of entire deformed region, highlighted by dotted gold box. .............. 95
Figure 48: As-sputtered microstructural characterization of films without elemental additions.
(a, b) top surface SEM micrographs with border color corresponding to (c) X-ray
diffractograms for samples deposited from the arc melted (red) or AM (grey) Inconel 718
xiii

targets. (d) Representative BF STEM micrograph of both samples in the as-sputtered state,
with growth direction indicated by the black arrow. .................................................................. 103
Figure 49: Microscopic characterization of Inconel 718 sample sputtered from the (left) arc
melted target and (right) AM target. (a) DF STEM micrograph with distribution of feature
sizes inset. Dotted gold box indicates area where TKD and EDS maps were acquired.
Average feature size provided below DF STEM micrograph. (b) TKD pattern for identified
phases. Inverse pole figures provided in bottom of figure. (c) EDS maps of major constituent
elements. White bars in TKD pattern and EDS maps represent 500 nm scale bar. .................... 106
Figure 50: NanoSIMS maps for constituent elements in each sample. Left column is the
sample deposited from the arc melted target, while the right column is the sample deposited
from the additively manufactured target. .................................................................................... 109
Figure 51: Microscopic characterization of Inconel 718 sample with Zr additions sputtered
from the (left) arc melted target and (right) AM target. (a) DF STEM micrograph with
distribution of feature sizes inset. Dotted gold box indicates area where TKD and EDS maps
were acquired. Average feature size provided below DF STEM micrograph. (b) TKD pattern
for identified phases. Inverse pole figures provided in bottom of figure. (c) EDS maps of
major constituent elements. White bars in TKD pattern and EDS maps represent 500 nm scale
bar. .............................................................................................................................................. 113
Figure 52: Microscopic characterization of Inconel 718 sample with Hf additions sputtered
from the (left) arc melted target and (right) AM target. (a) DF STEM micrograph with
distribution of feature sizes inset. Dotted gold box indicates area where TKD and EDS maps
were acquired. Average feature size provided below DF STEM micrograph. (b) TKD pattern
for identified phases. Inverse pole figures provided in bottom of figure. (c) EDS maps of
major constituent elements. White bars in TKD pattern and EDS maps represent 500 nm scale
bar. .............................................................................................................................................. 114
Figure 53: NanoSIMS maps for constituent elements in samples with Zr (above dotted black
line) or Hf (below dotted black line) additions. Rows (a) and (c) are samples deposited from
the arc melted Inconel 718 target while rows (b) and (d) are those from the AM target.
Regions of Ti and S enrichment in samples with Hf additions indicated by yellow circles. ...... 116
Figure 54: Representative load-displacement curves for sample S1-7Al-B ............................... 182
Figure 55: Representative load-displacement curves for sample S4-5Ti-T ................................ 182
Figure 56: Schematics of representative microstructures with nanoindentation load-
displacement curves. Column (a) is a NT microstructure, column (b) is the uniform HNM
microstructure, and column (c) is the gradient HNM microstructure. ........................................ 183

xiv

Abstract
Nanostructured materials have garnered significant attention due to their remarkable
properties in a wide variety of applications; however, the appropriate synthesis parameters for
improving multifunctionality in these materials are not yet fully understood. Therefore, a particular
emphasis must be placed on processing-microstructure relationships to guide the design of
nanostructured materials across various synthesis techniques. To do so, the development of widely
tailorable processing methods, capable of enhancing control over compositional resolution and
representative microstructural formation is crucial. In this dissertation, magnetron sputtering, a
physical vapor deposition (PVD) technique, is examined as a tool for designing nanostructured,
advanced engineering materials with increased compositional and microstructural complexity with
high precision. Deposition conditions are individually examined to identify their influence on alloy
development. Compositionally driven phase formation is evaluated within multi-principal element
alloys by using co-sputtering techniques, where distinct phase transition zones are identified and
correlated to the atomic characteristics of the alloying elements. Non-compositional effects on
microstructural formation are then investigated in Ni-superalloys by tailoring residual stresses via
the substrate type to induce unique distributions of heterogeneous nanostructures, which are found
to have significant influence over the mechanical performance of the alloy. All the controllable
parameters of magnetron sputtering are then combined with post-deposition heat treatment to
develop a comprehensive processing technique, in which representative microstructures across
different synthesis methods can be readily prepared and evaluated, particularly in the screening of
additively manufactured Ni-superalloys. Altogether, this dissertation highlights magnetron
sputtering as a highly tailorable and versatile synthesis method, which can then be leveraged as a
means of understanding complex processing-microstructure relationships in future developments
of advanced engineering materials.
1

1. Chapter 1: Introduction
Processing-microstructure relationships are a critical interconnection within the materials
science tetrahedron, explaining the complex interplay of how synthesis parameters can influence
the characteristics of materials. However, studies on these relationships have lagged in recent
materials science efforts, like the Materials Genome Initiative (MGI), due to high variability
amongst preferred processing methods. These limitations include differences in cooling rate
among synthesis techniques, chemical reactions, control over grain size, scalability, and
throughput. Therefore, a widely tailorable processing method capable of addressing these
limitations and traversing the entire synthesis space is needed.
A possible candidate is magnetron sputtering, a physical vapor deposition (PVD) technique.
Magnetron sputtering is a highly tunable processing method, capable of fabricating films
composed of nearly any alloy, element, or ceramic material with customizable deposition
parameters. These controllable factors make magnetron sputtering an advantageous method for
producing uniform microstructures with tailorable grain sizes and orientations over large,
industrially scalable areas with variable film thickness, ranging from sub-nanometers to hundreds
of microns. While the rapid cooling rate of magnetron sputtering facilitates microstructures that
are typically metastable, single-phase solid solutions with uniform composition, in-situ heating or
post-deposition heat treatment brings these metastable microstructures to an equilibrium state. This
fully comprehensive processing method allows for the development of representative
microstructures to investigate microstructural, thermodynamic, and mechanical trends and
phenomena for both bulk and nanoscale materials.
The design of nanostructured materials is of particular concern in this work, as there is still a
need to improve their multifunctionality. A possible avenue for expanding the usage and design of
nanostructured materials is introducing increased complexity, either compositionally or
microstructurally. Conventional alloying has long been utilized as a means of improving material
properties, and the field of nanostructured materials is no exception. For example, the synthesis of
binary and ternary alloy arrangements, in an effort to stabilize grain boundaries, has been explored
as a solution to improve thermal stability in nanostructured materials. Recently, increasing the
number of alloying elements beyond a ternary arrangement has been examined as a means of
improving nanostructured material capabilities, as a wider composition space with more unique
2

microstructures has been shown to be thermodynamically plausible. Multi-principal element alloys
(MPEAs), which are known for their “compositional complexity”, are thus a candidate for
enhancing nanostructured materials through alloying. Furthermore, microstructural complexity,
such as nanosized heterogeneous features, has also been investigated as a means of facilitating
multifunctionality in nanostructured materials, including improved thermal stability and strength-
ductility synergy. By employing a versatile synthesis technique like magnetron sputtering,
complex material spaces can be thoroughly explored. Processing inputs, including target power,
magnetron configuration, residual stresses, and post-deposition heat treatments, can be utilized to
develop structural heterogeneity, including multiple phases, gradient microstructures, and
nanosized features such as nanotwins. Coupled with extensive microscopic and mechanical
characterization, the microstructural evolution of complex materials can be explored with atomic
resolution. These efforts can then be used to close the processing-microstructure-properties-
performance loop by determining the appropriate synthesis conditions for desirable material
behavior, thereby promoting the design of advanced materials.

3

2. Chapter 2: Background

2.1. Nanostructured Materials
Nanostructured materials have been of considerable interest due to their notable properties,
which can be attributed to reduced feature sizes (typically in the range of 1 to 100nm) [1], and high
density of interfaces [2]. These interfaces, such as grain boundaries, impede dislocation movement,
while smaller features improve fracture toughness by reducing crack initiation site sizes. Grain
boundary strengthening can be quantified by the Hall-Petch relationship, which relates average
grain size to material strength:
𝜎 𝑦 = 𝜎 𝑜 +
𝑘𝑦
√ 𝑑 (1)
Where σy

is the yield strength of the material, σo is the single crystal strength of the material, ky is
the strengthening coefficient, and d is the average grain diameter. Under this principle, yield
strength increases as the grain size decreases. Governed by the Hall-Petch relationship,
nanostructured materials exhibit excellent strength compared to conventional bulk metals and
metal alloys. It should be noted that this relationship only holds up to a critical grain size as
experimental studies have shown that as the grain size approaches 10 nm, the strengthening
mechanisms deviate from this trend due to additional competing factors affecting overall strength,
such as grain boundary sliding [3].
The continued motivation for studying nanostructured materials lies in their potential
versatility and multifunctionality with a wide variety of applications, including microelectronics,
quantum computing, tissue engineering, biotechnologies, and clean energy [4]. However, poor
thermal stability and brittle mechanical behavior currently limit their potential for broad
applications and are still being addressed. To resolve these issues, the design of nanostructured
materials with structural or compositional complexity, coupled with high-throughput screening
and synthesis techniques, must be employed to explore the breadth of the material genome for
possible solutions. The typical synthesis techniques for fabricating nanostructured materials are
examined in the next section.

4

2.2. Synthesis Techniques
A wide range of preparation techniques are available to synthesize nanostructured materials
for various applications, length-scales, energy requirements, and costs. Most notably, these include
mechanical alloying [5], thermal spraying [6], severe plastic deformation (SPD) [7],
electrodeposition [8], and vapor deposition [9, 10]. Some of these techniques have been shown to
be industrially scalable and have certain advantages and disadvantages [11]. Mechanical alloying
is popular due to its versatility and ease of use; however, grain coarsening and contamination can
occur during powder consolidation and preparation [12-14]. SPD utilizes a straightforward
relationship between strain and grain size to synthesize samples but can only be performed on
small scales [7]. Although thermal spraying offers high deposition rates and near net-shape
coating, it is constrained by non-uniform grain size distribution and void formation [6].
Electrodeposition is useful for obtaining uniform grain sizes, yet is limited compositionally by
given chemical reactions [8]. Another challenge in synthesizing nanostructured materials is
discrepancies in structural formation between different processing techniques, such as
microstructural variations, defects, and impurities. Non-uniform microstructure and morphology
can result in substantial deviations in structure-sensitive mechanical properties of the material [15].
As exhibited in Figure 1, disparities in the microstructure of the same material produced by ball
milling, electrodeposition, and sputtering are quite stark. As a result, trends across synthesis
techniques must be carefully considered.
Figure 1: TEM micrographs of nanostructured Ni samples synthesized via (a) ball milling, (b) electrodeposition, and
(c) sputtering [16].
5

In contrast to the previously discussed techniques, vapor deposition can synthesize
nanostructured materials with increased structural uniformity and fewer impurities as a result of
its well-controlled and isolated working environments [11]. Physical vapor deposition (PVD)
relies on the removal of atoms from a solid or a liquid by energetic means, which then travel across
an evacuated chamber and impinge on a solid surface, resulting in the formation of a film [17].
Types of PVD processes include thermal evaporation, physical sputtering, laser ablation, and arc-
based emission. Magnetron sputtering is of particular interest in the current work, as it has been
explored as a versatile method for producing representative nanostructured materials for proof-of-
concept experimentation.

2.2.1. Magnetron Sputtering
Magnetron sputtering covers a wide range of potential applications, including protective wear
and corrosion resistant coatings, mechanical coatings to enhance material strength,
optoelectronics, MEMS, NEMS, and micro/nanoelectronics [18]. In magnetron sputtering, high-
energy ionized particles are used to bombard the surface of a metal target. In this process, atoms
are removed from the target material, forming a metal vapor within the sputtering chamber that
deposits onto and coats a substrate as the vapor condenses. This technique allows for the deposition
of nearly any element or alloy and allows for extensive control over the microstructure of the
sputtered coating [19]. Control factors such as working pressure, substrate temperature, working
distance, and power input must be carefully maintained to ensure coatings are deposited uniformly,
and can be adjusted to influence microstructural formation. As a result, magnetron sputtering is an
advantageous technique for producing uniform microstructures with tailorable grain sizes [20],
which is critical in nanostructured material synthesis.
The work on microstructural formation in magnetron sputtered coatings by Thornton
emphasizes the importance of processing inputs on film growth and microstructure, particularly
substrate temperature and working gas pressure. Four distinct structure “zones” have been
identified based on the gas pressure and homologous temperature, as exhibited by Figure 2 [21].
In zone 1, the structure is columnar, consisting of tapered units defined by voided growth
boundaries. The structure in zone 2 consists of columnar grains, defined by grain boundaries that
increase in width with increasing temperature. Zone 3 consists of equiaxed grains that form under
6

high temperature conditions. Zone T is considered a transition zone between zones 1 and 2,
featuring a dense array of poorly defined fibrous grains [21, 22]. Based on these foundational
studies, it has been determined that homologous temperature and gas pressure have an inverse
relationship, such that increased temperature and reduced gas pressure increases grain size and
reduces void formation, and vice versa [21]. Therefore, the sputtering parameters must be
strategically selected and maintained for desired film formation. As will be discussed later, control
over sputtering parameters, coupled with Thornton’s zone map, can be leveraged to introduce
structural complexity during film formation.

Figure 2: The Thornton diagram, describing microstructural formation in magnetron sputtered films as influenced by
argon pressure and substrate temperature. Based on the figure, there are four distinct zones with variations in film
growth structure: zones 1 and 2 (columnar grain growth), zone 3 (equiaxed grain growth), and zone T (transition
between columnar and equiaxed growth) [21].

As noted earlier, magnetron sputtering is useful for manipulating material composition during
synthesis, able to deposit nearly any alloy, element, or ceramic [19]. Co-sputtering configurations,
7

in which multiple magnetrons are employed to deposit an alloyed film, can further enhance
magnetron sputtering as a tool for studying vast composition spaces by increasing control over
stoichiometry [23]. Alloying has long been considered an essential technique for improving the
multifunctionality of materials. In the case of nanostructured materials, it has been hypothesized
that alloying is a possible remedy for poor thermal stability [24, 25]. Therefore, the functionality
limitations of nanostructured materials can possibly be resolved by utilizing magnetron sputtering
to produce novel nanosized alloy configurations.

2.2.1.1. Nanostructured alloys synthesized via magnetron sputtering
Magnetron sputtering has long been considered an excellent technique for producing alloy
configurations with very fine grains [26]. These outcomes are due to the combined effects of ion
bombardment and “mixing processes”, as coined by Musil and Viček [27]. Sputtering parameters
influence the degree of ion bombardment, which is the act of sputtered ions impinging on the
surface of a substrate, affecting the film formation as the atoms coalesce [28]. This mechanism is
a non-equilibrium process, where the kinetic energy of the bombarding ions is directly transferred
into very small areas upon impact. As a result, ion bombardment is affiliated with extremely high
cooling rates (10
9
– 10
11
K/s) [29], making it possible to produce dense films corresponding to
Zone T, Zone 2, and Zone 3 structures in the Thornton structural map when sputtering is carried
out at low pressures, as seen in Figure 2 [21]. Due to the rapid cooling rates, grain growth is
impeded, allowing for the formation of nanocrystalline films [27].
Mixing processes refer to the addition of one or several elements to a base, single element
material, (i.e., alloying) which can be leveraged to control structural and phase formation in films.
Atomic characteristics of the mixing elements, such as miscibility and enthalpy of alloy formation,
influence the synthesis of nanocrystalline films and the ultimate alloy structure formed by the
deposition process [27]. For example, previous research on sputtered pure Ti films show that the
resultant microstructure is always a coarse grained polycrystalline structure; however, the
incorporation of a high content (>10 %) of additional elements can lead to nanocrystallinity [30,
31]. Furthermore, solid solution forming ability is dictated by the Hume-Rothery rules, namely
atomic size difference, electronegativity difference, and valence electron concentration of the
8

alloying elements. Certain criteria for each of these parameters must be fulfilled to form single
phase alloys [32], therefore careful consideration must be placed during alloy engineering.
The combination of ion bombardment and mixing processes is exemplified by the alloying
of a film via co-sputtering configurations, in which multiple elements are deposited and mixed to
ultimately form an alloyed film. In a co-sputtering configuration, the atomic ratio of alloying
elements can be independently controlled by adjusting target sputtering power [33]. The use of
different cathodes allows for tunable compositions [34, 35], material doping [36], embedding of
nanoparticles [37], formation of alloy-compounds [38], and the synthesis of multilayers [39-42] or
nano-laminates [43, 44]. This sputtering method has been widely explored as a means of forming
nanocrystalline binary [45-49] and ternary alloys [50-52]. A schematic of a binary co-sputtering
configuration is included in Figure 3.
Figure 3: Schematic of co-sputtering configuration of a binary alloy [53].

While significant work has been done to model binary alloys for improving nanostructured
material stability [54-60], ternary alloys substantially increase the number of different accessible
nanostructure configurations, as the topological and phase complexity available with three species
9

compared to two is much higher [61]. Thus, many more unique microstructures are expected to be
thermodynamically plausible. This approach opens the door for future research on magnetron
sputtered alloys with increasing compositional complexity [61], with the possibility of achieving
new levels of thermal stability [26]. Moreover, the ability to explore expansive composition spaces
grants the opportunity to search for the best configurational solutions for optimizing alloyed
nanostructured materials, no matter the compositional complexity.

2.3. Films with compositional complexity: multi-principal element alloys (MPEAs)
As previously mentioned, the alloying of nanostructured materials has been considered as a
possible remedy for poor thermal stability. Some studies have suggested that alloying may stabilize
nanometer-sized grains via grain boundary segregation, while also providing additional strength
via grain-boundary and solid solution (SS) strengthening mechanisms [24, 25]. This concept can
be taken further by introducing the fundamentals of multi-principal element alloys (MPEAs) to
the field of nanostructured materials. MPEAs are known for their “compositional complexity”,
referring to the presence of four or more alloying elements that are between 5 at% and 35 at% of
the total composition. These types of materials include both high entropy alloys (HEAs) and
compositionally complex alloys (CCAs). It is believed that imparting compositional complexity
in nanostructured materials can improve their multifunctionality. For example, while conventional
alloys can experience recrystallization and grain growth at elevated temperatures, which can
reduce material strength [62], nanostructured MPEAs have been found to retain grain-boundary
induced strengthening at elevated temperatures, with yield strengths an order of magnitude higher
than coarse-grained counterparts and five times higher than single crystal equivalents [63].
In traditional alloying, a material typically consists of a singular base element, whose
properties are enhanced by the addition of relatively small percentages of other elements, but
nevertheless retains the characteristic properties of the base material. Conversely, MPEAs feature
multiple principal elements such that no component’s individual properties dominate the system.
This type of configuration leads to unique and notable mechanical and physical properties. For
example, the Ashby diagram in Figure 4 plots a variety of materials based on their respective yield
strength and fracture toughness. MPEAs, highlighted in orange, occupy the space in the upper
right-hand corner of the graph, exemplifying their excellent mechanical properties compared to
10

other materials. It has also been reported that certain MPEA configurations exhibit resistance to
wear [64-67], oxidation [68, 69], and corrosion [70-73], biocompatibility [74], and feature unique
electromagnetic properties [73, 75-77]. Furthermore, the departure from a single base element
offers the possibility of tailoring physical properties, including stiffness [78].
Figure 4: Ashby diagram comparing fracture toughness and yield strength for a variety of materials. MPEAs are
notated in orange [79].

The notable material properties observed in MPEAs are due to four core effects, which are
outlined in the seminal paper by Yeh et al. [80]. They include high entropy, sluggish diffusion,
severe lattice distortion, and “cocktail effects”, which refer to the innate complexity of predicting
material properties in a configurationally complex material. Each of these effects is believed to be
caused by size mismatch and the quantity of alloying elements. This concept is illustrated in Figure
11

5, which contrasts a dilute alloy solution with an MPEA solution. In a traditional solid solution,
solute atoms are constrained to occupy lattice sites by surrounding solvent atoms. By contrast,
atom positions usually deviate from their traditional lattice sites in MPEA solutions, which
increases lattice distortion and excess configurational entropy compared to traditional alloys [81].
Together, these core effects can be used to predict the material properties of certain alloy
configurations [11]. Sluggish diffusion, severe lattice distortion, and cocktail effects will be briefly
discussed in the next few sections, while more time will be spent on the role of high entropy, as
studies have claimed this effect to be the dominant factor controlling MPEA material properties.
Figure 5: The effect of atom size difference on atom positions in (a) a dilute solution and (b) an MPEA solution. The
variability in atom positions in (b) contribute to an excess configurational entropy [81].

2.3.1. The sluggish diffusion effect
The sluggish diffusion effect is believed to contribute to high temperature strength [82, 83]
and stability [84, 85] in MPEAs, as well as the formation of nanostructures [86-88]. Previous work
has found that the self-diffusion coefficient is much lower in MPEAs than in traditional alloy
arrangements, indicating that atoms diffuse at a slower rate [80, 89]. In MPEA configurations,
there is a greater variety of atoms surrounding lattice sites than in conventional alloys. Since each
site is surrounded by different atoms, variations in bond configurations and lattice potential energy
(LPE) exist [90]. Both vacancy formation and migration enthalpies are related to local atomic
interactions [90-92]; therefore, the variations in LPE changes diffusion kinetics. Fluctuations in
LPE can occur when an atom traverses from one site to another, which is a result of the difference
12

in total interaction energy from site to site. When the LPE for an element site decreases, the site
becomes an “atomic trap”, in which the energy barrier and activation energy required for diffusion
increase. As a result, atom migration is inhibited and results in the sluggish diffusion of MPEAs
[89].

2.3.2. The severe lattice distortion effect
As shown in Figure 5, MPEA solutions feature atoms with varying atomic size, such that
none of the atoms sit perfectly on their ideal lattice sites, giving rise to considerable lattice
distortion effects. These effects are attributed to many thermodynamic and kinetic mechanisms in
MPEA configurations, including induced strain, increased total free energy [93] and
configurational entropy [81], hindered dislocation motion, which results in solid solution
strengthening [94], and slowed crystal growth rate, leading to nanosized structures [95].
Furthermore, lattice distortion can contribute to phase formation [23, 65, 96-98], as high distortion
leads to lattice collapse, causing the nucleation of amorphous phase structures, as seen in some
previously reported systems [99-101]. Additionally, lattice distortion effects lead to increased
scattering of propagating electrons and phonons, which translates to lower electrical and thermal
conductivity [102]. Both empirical [103] and theoretical [104] models have been employed in an
effort to quantify lattice distortion and use it to predict phase formation in MPEA systems, and
while these models have shown strong correlations, as exhibited in Figure 6, more factors must be
considered for accurate predictive purposes [81].

13

Figure 6: Correlation between the root mean square residual strain ε RMS (theoretical model) and atomic size difference
δ (empirical model) for a variety of metallic glass forming alloys [105].

2.3.3. “Cocktail effects”: The interaction of alloying elements
Coined by Ranganathan, the term “cocktail effect” refers to the composite effect that
MPEAs exhibit due to the interaction of unique elements with different material characteristics
[106]. Unlike the other core effects, the cocktail effect is not a hypothesis; it serves as a reminder
that exceptional results can come out of unexpected synergies, especially in the vast composition
space of MPEAs [81]. One example cited in the literature to describe the cocktail effect is the
influence of Al on microstructure and hardness in the AlxCoCrCuFeNi MPEA system. Since Al is
a soft FCC metal, it would be easy for one to believe that subsequent Al addition would cause
material softening and a retention of the FCC phase. However, the addition of Al in this alloy
system results in the transition to a BCC structure and increased hardness, as visualized in Figure
7. Due to its large atomic size compared to other alloying elements, the addition of Al causes lattice
distortion, thus increasing the strength of the material. Simultaneously, the Al has stronger
cohesive bonding with the other elements, also contributing towards improved strength [94]. In
summary, the cocktail effect suggests that unexpected results can occur in novel material
combinations.

14

Figure 7: Hardness as a function of Al content in the Al xCoCrCuFeNi MPEA system [94].

2.3.4. The high entropy effect
At the onset of the MPEA field almost two decades ago, the high entropy effect was
believed to be the most notable out of the four core effects outlined previously. This effect proposes
that increased configurational entropy may favor the formation of single-phase solid solutions (SS)
over intermetallic (IM) solutions [81]. Using the Gibbs free energy equation:
𝐺 = 𝐻 − 𝑇𝑆 (2)
Where H is the enthalpy, T is the temperature, and S is the entropy, solid solution phase formation
can be promoted by reducing the Gibbs free energy via increasing the configurational entropy S.
By designing alloys in near equiatomic elemental ratios, the configurational entropy can be
increased, as proposed by Boltzmann in his hypothesis on the relationship between entropy and
system complexity [107]:
∆𝑆 = −𝑅 ∑ 𝐶 𝑖 𝑖 𝑙𝑛 𝐶 𝑖 (3)
Where R is the universal gas constant and Ci is the molar content of the i
th
component. Mixing
entropy can then be maximized when N alloying elements are in equiatomic ratios:
15

∆𝑆 = 𝑅 𝑙𝑛 𝑁 (4)
The early “high entropy” definition stated that alloys must contain 5 constituent elements with an
entropy exceeding 1.61R for the material to be considered a “high entropy alloy”. This concept
can be seen in Figure 8, where the x-axis is the number of constituent elements and the y-axis is
the entropy of mixing [107]. A high mixing entropy can reduce the number of generated phases
according to the Gibbs phase law, which improves the compatibility of the components, thus
facilitating stable and simple phase formation [93].
Figure 8: Plot of entropy of mixing v. number of alloying elements. Zones for low, medium, and high entropy alloys
are indicated [107].

It was originally thought that SS phases were stronger and more capable of retaining
ductility and damage tolerance, while IM phases increased brittleness and caused processing
issues. As a result, most of the initial work in the field fixated on producing SS phases via high
entropy alloying [80, 108, 109]. However, more recent work has found that it is not just increased
configurational entropy that leads to SS phases, but a balance of the entropy of mixing and enthalpy
of mixing [81]. In fact, a study by Senkov et al. reported that increasing the number of alloying
16

elements, in an effort to maximize configurational entropy, favors the formation of IM compounds
over SS phases [110]. Moreover, limiting alloy configurations to only those with SS phases and
equiatomic arrangements reduces the discoverable composition space and may hinder alloy
optimization. Indeed, in some instances it may be beneficial to develop MPEAs with multiphase
microstructures or intermetallic compounds, as they have been shown to improve structural
properties at high temperatures [79, 111] as well as the balance of strength and damage tolerance
[81, 111]. Thus, the potential of the field for practical scientific purposes can be best unlocked by
traversing the entire “hyper-dimensional” composition space, as coined by Miracle et al. [81],
emphasizing the need for studying compositionally complex alloys.

2.3.5. Compositionally complex alloys (CCAs)
Although both HEAs and CCAs contain four to five or more alloying elements between 5
and 35 at% of the total composition, CCAs do not need to be equiatomic nor do they need to
include SS phases [112, 113], which may promote a greater balance of properties [114]. Some
non-equimolar compositions have been shown to have better mechanical or physical performance
compared to their equimolar counterparts [115, 116] and conventional alloys alike [117]. For
example, in a comparison of CrNbTaVW1.7 to the equimolar CrNbTaVW, it was found that the
additional W contributed to improved flexural strength, strain to fracture, and toughness despite
similar multiphase microstructures [118]. The comparison of flexural strength for these two
samples across a range of temperature values can be observed in Figure 9a. Speaking of multiphase
microstructures, the presence of secondary phases, precipitates, and spinodal structures may
promote more strengthening mechanisms and improved mechanical performance in CCAs
compared to HEAs. While the mechanical properties of SS HEAs are controlled by three of the
five classical strengthening mechanisms including solid solution hardening, work hardening, and
Hall-Petch hardening, these mechanisms degrade at elevated temperatures due to recovery,
recrystallization, grain growth, and diffusive drag of solute atoms [117]. By contrast, it has been
reported that certain non-equimolar CCA arrangements have superior structural properties at
elevated temperatures [82, 119, 120]due to the other two classical strengthening mechanisms,
precipitate and Orowon strengthening, which are provided by high volume fractions of IM phases.
Precipitate and Orowon strengthening mechanisms can retain effectiveness at high temperatures
17

[111], emphasizing the importance of secondary phases in alloy arrangements depending on the
application. For example, in the review by Manzoni and Glatzel, it was found that non-equiatomic,
multiphase Al7Co23Cr23Fe23Ni23 (FCC + BCC + B2) and Al10Co25Cr8Fe15Ni36Ti6 (FCC + L12 + C1)
exhibited the best mechanical performance in a group of HEAs and CCAs under tension at RT and
700⁰C, respectively, thanks to microstructures that are comparable to Ni-superalloys [112]. The
strength and ductility for these CCA systems are mapped in the plot in Figure 9b.
Figure 9: (a) flexural strength-fracture strain of CrNbTaVW and CrNbTaVW 1.7 samples at 298 K, 673 K and 873 K
[118]. (b) UTS versus tensile ε f at room temperature of heat-treated alloys in a state close to
equilibrium. Al 7Co 23Cr 23Fe 23Ni 23 alloy, hcp and fcc, alloys with eutectic-like microstructures, L1 2 in
fcc, single phase alloys [112].

Furthermore, CCAs offer unique functional properties including corrosion resistivity and
pitting potentials in the range of stainless steels [71], better performance against irradiation
induced swelling damage compared to currently used alloy arrangements under similar exposures
[121], and magnetic properties, due to high coercivity when compared to other high-performance
magnets [114]. Thus, the departure from strict alloy definitions in the realm of MPEAs is critical
for alloy optimization.
In summary, magnetron sputtering is a useful technique for producing materials with
nanosized features and compositional complexity, namely MPEAs. These materials feature a wide
range of desirable properties, characterized by sluggish diffusion, severe lattice distortion, high
entropy, and “cocktail” effects. Nanostructured materials can also be optimized through the
development of microstructural complexity during sputtering. Using both compositional and
microstructural complexity in alloy development can expand the accessible material property
space, granting the opportunity to develop materials with even better performance qualities.
18

2.4. Film Microstructural Space
So far, it has been established how film properties can be enhanced by imparting compositional
complexity via magnetron sputtering techniques. In addition to compositional variation,
magnetron sputtering can be utilized to introduce microstructural complexity, including nanoscale
features, gradient microstructures, nanotwins, and structural heterogeneity. In the next sections,
microstructural formation in films will be discussed, with emphasis on how to promote the
formation of structural complexity outside of conventional film microstructures. Several types of
microstructurally complex materials will then be examined.

2.4.1. Microstructures of films
The growth processes that control microstructural evolution in films proceed through
consecutive stages of nucleation, island growth, coalescence of islands, formation of
polycrystalline islands and channels, development of continuous structure, and film growth [122,
123]. These film formation mechanisms are driven by thermodynamic processes, allowing for the
evolution of the size and morphology of the grains. The thermodynamics are dictated by the
competition between surface free energy and bulk free energy of the particles that make up a grain
[124], as seen in Equation 5:
∆𝐺 = 4𝜋 𝑟 2
𝛾 +
4
3
𝜋 𝑟 3
∆𝐺 𝑣 (5)
Where ΔG is the total free energy, r is the radius of a spherical particle, γ is the surface free energy,
and ΔGv is the bulk free energy of a crystal. Since γ is always positive and ΔGv is always negative,
it is possible to find a critical free energy, corresponding to a critical radius at which a particle can
survive without being dissolved or subsumed by larger particles [124], as derived in Equation 6
and visualized in Figure 10:
𝑟 𝑐𝑟𝑖𝑡 =
−2𝛾 ∆𝐺 𝑣 (6)
19

Figure 10: Free energy diagram for nucleation, identifying a critical radius. ΔG is the total free energy, ΔG s is the
surface free energy, ΔG v is the bulk free energy, G crit is the critical free energy, and r c is the critical radius [124].

This phenomenon is seen in Ostwald ripening [125]. Smaller particles, due to their high
solubility and surface energy, will redissolve and allow larger particles to grow even more [124].
Grains will selectively shrink or expand during the coalescence stage of film formation [123] to
reduce total free energy, ultimately resulting in an average increase in grain size [126]. A schematic
of grain growth during film formation is provided in Figure 11. The transition from Figure 11a to
Figure 11b highlights how larger grains preferentially grow while smaller grains preferentially
shrink.

20

Figure 11: Top view illustration of a thin film undergoing normal grain growth. Large grains tend to grow larger and
small grains shrink and disappear, such that average grain size increases over time [126].

In thin films, grain growth occurs preferentially in grains with orientations that have low
surface and interface energies. The reduction of surface and interface energy thus leads to the
distribution of non-random crystallographic orientations in the film and the development of
preferred orientations or textures [127]. An example of preferred orientation is the (111)
orientation in FCC metals [127, 128], which is the lowest surface energy orientation for those type
of materials. Polycrystalline films also tend to have high strain energy density due to high yield
stresses [129, 130]. Any elastic anisotropy that exists in the film can then cause a gradient of strain
energy density between grains. Grain growth serves as a thermodynamically favorable mechanism
for minimizing strain energy in the film, contributing to the development of a strain energy
minimizing texture [131-133]. Like grain morphology, texture and crystallography can influence
the properties of a material as well.
Although strain energy minimization and surface and interface energy minimization both
favor the development of texture through preferred growth of grains with specific orientations, the
textures resulting from these two mechanisms are generally not the same. As a result, grain growth
in films is viewed as abnormal, as the growth of sub-populations of grains with specific
21

orientations is favored either by surface and interface energy or strain energy minimization,
leading to a bimodal distribution of grains [126]. During film growth, surface and interface
minimization is favored at low strain values and during deposition at high temperatures [128].
Strain energy minimization, on the other hand, occurs when films are deposited at temperatures
well below grain growth temperatures or during post-deposition annealing processes [127].
Nevertheless, grain growth is the leading mechanism for reducing total film energy and developing
restricted orientations in films. Thus, it is critical to tailor the film synthesis conditions to
manipulate the grain geometry, size, distribution, and orientations to control film microstructure
and optimize material properties.
In the case of magnetron sputtering, the distribution of crystallographic orientations can be
influenced by processing parameters, substrate characteristics, energetic ion bombardment,
geometric conditions, and heat treatments [128]. These processing inputs can adjust preferred
growth texture, crystal structure, introduce defects, manipulate interfaces, and ultimately increase
the complexity of the film microstructure. Coupled with effects from intrinsic stresses during film
growth, structural inhomogeneity can be introduced throughout the film thickness by tailoring the
processing conditions.

2.4.2. Microstructural complexity
As previously mentioned, nanostructured materials are characterized by a high density of
interfaces, proven to fortify mechanical performance. However, interfaces also carry an energetic
penalty that drives grain boundary mobility, leading to thermodynamically unstable
microstructures. As it turns out, the driving force for grain growth varies greatly depending on
interface type and structure [134, 135], while the segregation of secondary phases to interfaces has
been shown to reduce grain boundary energy or mitigate grain boundary mobility [136]. Therefore,
significant attention must be paid to tailoring interfaces for improving the performance of
nanostructured materials, as microstructures can be stabilized by introducing structural complexity
at the interfaces.
The distribution and structure of interfaces are critical to bulk film performance, as
interfaces feature a wide variety of energies and properties [137, 138]. The fields of grain boundary
engineering and grain boundary segregation engineering each seek to manipulate interfaces for
22

improving material performance. In the former, the effort is to produce microstructures with a high
density of low-energy interfaces with unique characteristics [139, 140], such as grain boundaries
with a likely propensity of twinning, while the latter aims to decorate interfaces with solutes, which
can affect their energy, mobility, and structure [141, 142]. Each of these approaches inherently
introduces structural complexity outside of typical film microstructures, as they alter morphology,
preferred texture, and crystallography.
Microstructurally complex materials have been shown to exhibit better performance
compared to both coarse grained and homogeneous nanocrystalline materials. Two examples of
structurally complex materials include nanotwinned (NT) [143-147] and heterogeneous
nanostructured materials (HNMs) [148-150]. Nanotwins have been shown to improve strength and
provide acceptable ductility in FCC metals [148], improve corrosion resistivity [151], thermal
stability [152], and tolerance to radiation damage [153], while HNMs are notable for improving
strength-ductility synergy [154]. Each of these microstructurally complex materials will be
explored in more detail in the following sections.

2.4.2.1. Nanotwinned (NT) Materials
Nanotwinning in materials is identified in grain boundaries as a shifted segment of a crystal
where crystal lattices on each edge are linked across a twin plane by mirror symmetry [155].
During film growth, small “islands” of atoms nucleate, grow, and coalesce to form the resultant
microstructure. The grains then have a given probability of containing either stacking faults (SF),
which are crystallographic defects characterized by stacking plane interruptions [128], or twin
boundaries (TBs), which are specifically structured to follow the ordered arrangement of nano-
scale twin lamellae [156]. The difference between these two types of boundaries is depicted in
Figure 12, where Figure 12a is a conventional grain boundary while Figure 12b is a nanoscale twin
boundary.

23

Figure 12: schematic of a (a) conventional grain boundary and (b) nanoscale twin boundary. The red ┴ symbol denotes
dislocation motion, “d” represents the grain size, and λ denotes twin thickness [156].

The probability of twin nucleation, ρ, is based on the model proposed by Zhang et al., as
seen in Equation 7:

𝑟 𝑡𝑤𝑖𝑛 − 𝑟 𝑝𝑒𝑟𝑓𝑒𝑐𝑡 𝑟 𝑝𝑒𝑟𝑓𝑒𝑐𝑡 =
∆𝑟 𝑟

∆𝐺 𝑉 =
𝐾𝑇
𝛺 ln ( 𝐽 √
2𝜋𝑚𝐾𝑇 𝑃 𝑆 )

𝜌 =
∆𝑟 𝑟 =
𝛾 𝑡𝑤𝑖𝑛 ℎ∆𝐺 𝑣 (7)
Where reprfect is the critical radius of a perfect nucleus, rtwin is the critical radius of a nucleus with
a stacking fault defect, γtwin is the twin boundary energy (approximated as half the stacking fault
energy (SFE)), h is the interplanar spacing, ΔGv is the bulk free energy per unit volume, K is
24

Boltzmann’s constant, T is the temperature, Ω is the atomic volume, J is the deposition flux, m is
the atomic mass of the interacting species, and Ps is the vapor pressure above the solid [157]. For
a high rate of nanotwin nucleation, the value of Δr/r must be less than 5% [158]. Using Equation
7 to solve for ρ, the resultant grain boundary type is thus dependent on three parameters: SFE of
the material, deposition flux, and deposition temperature [145]. An example of NT microstructures
deposited with varying conditions is included in Figure 13. The figure highlights how materials
with different SFE (i.e. CuAl v. CuNi) or synthesized under different deposition conditions can
influence qualitative microstructure, twin thickness, and preferred texture [144].

25

Figure 13: Cross-sectional bright field TEM comparing as-sputtered (A) Cu2Al-A (λ=5 nm), (B) Cu2Al-B (λ=18 nm),
(C) Cu10Ni-A (λ=13 nm), and (D) Cu10Ni-B (λ=31 nm); and (E) representative XRD scans of the NT alloys. The
arrow to the left indicates the film growth [144].

Increasing deposition rate and/or deposition temperature and decreasing SFE can increase
the probability of twin nucleation. Since SFE is a material property, synthesis by high deposition
rate, a controllable parameter, can be used to achieve microstructures not previously observed,
such as heterogeneous NT microstructures in high SFE materials [146]. Using this model, NT
26

structures can be more readily designed and tailored, highlighting a controllable technique for
improving mechanical performance in nanostructured materials.

2.4.2.2. Heterogeneous Nanostructured Materials (HNMs)
Much like contemporary materials, the trade-off for the increase in strength of
nanostructured materials is that they can become quite brittle with decreasing grain size and feature
limited ductility. This is due to poor strain hardening, which is caused by dislocations traversing
the relatively small grains and annihilating into surrounding interfaces [148]. It is possible that
under tensile loading, these nanostructured materials can experience early necking due to strain
localization, which activates prior to expected plastic deformation. As a result, the material will
undergo cracking until final failure is reached without much plastic deformation occurring [154].
One field of research that seeks to circumvent this phenomenon is the development of
heterogeneous nanostructured materials (HNMs), which are comprised of both hard (smaller grain
size) and soft (larger grain size) domains. Since the soft domains deform more plastically than the
hard domains, a plastic gradient forms, requiring the storage of geometrically necessary
dislocations (GNDs), which contribute to work hardening [149]. The characteristic length scale of
gradient plastic deformation, λ, is determined by the spacing between neighboring soft and hard
regions. HNMs are characterized by an unusually small λ, and thus offer a high capacity of storing
more GNDs, thereby enhancing the strain hardening ability of the material [149]. As a result, the
strength-ductility synergy is resolved, such that a material can feature both high strength and high
ductility. It should be noted that careful attention must be paid to the distribution of these hard and
soft domains, which can affect the degree of GND pile-up [150]. In Figure 14, it can be seen how
a random assortment of these domains has a negative influence on mechanical behavior (labeled
CG + NG or Coarse Grained + Nanograined), while a gradient distribution of domains (labeled
GNGs or Gradient Nanograined Structures) results in strength-ductility behavior that occupies a
white space of the material genome.
27

Figure 14: Strength-ductility plot comparing heterogeneous nanostructured materials (GNGs) to other conventional
nanostructured materials, such as coarse-grained (CG) and nanograined (NG) structures. We can see that GNGs exist
in an otherwise unexplored space of strength-ductility synergy within the material genome [154].

Since the field of HNMs is relatively unexplored, many possible avenues of material
selection and microstructural design are still available. One direction to take is examining
heterogeneous behavior in coarse grained materials and translating it to the nanoscale. A promising
material candidate is Ni-based superalloys, including Inconel 718 and Inconel 725, which feature
both high strength and corrosion resistivity [159]. The main difference between these alloys lies
in the composition of their trace elements; Inconel 725 tends to have higher Mo content (7-9.5
wt.% compared to 2.8-3.3 wt.%), which contributes to improved corrosion resistivity [160, 161].
The acceptable composition ranges for the two alloys are provided in Table 1.
28

Table 1: Comparison of standard composition ranges for Inconel 718 and 725, provided in wt.% [161, 162], where
“Bal*” refers to balance.
Standard Composition Ranges for Inconel 718 and 725 (wt.%)
Alloy Ni Cr Mo Fe Nb Ti Al Si
Inconel
718
50-55 17-21 2.8-3.3 Bal* 4.8-5.5 0.7-1.2 0.2-0.8
0.35
max
Inconel
725
55-59 19-22.5 7.0-9.5 Bal* 2.8-4.0 1.0-1.7 0.0-0.35
0.20
max

Since the compositional differences between the two alloys are minimal, each alloy
features similar precipitation behavior. The industry standard heat treatment of both alloys
facilitates the precipitation of Ni3Nb dispersoid γ”, which can greatly improve the yield and tensile
strength of the material [159], Ni3(Al, Ti) γ’ precipitates, which enhance strength at elevated
temperatures [163, 164], and carbide precipitates that preferentially form at high angle grain
boundaries [165] and improve the thermal stability of the material [136], making for useful
complex structures. However, the introduction of stored energy or stress gradients in the material,
whether intrinsically, thermally, or from mechanical deformation [166] can cause the nucleation
of heterogeneous microstructures outside of typical γ”, γ’, and carbide formation. It has been
reported that rafted structures, δ-phase precipitates, and abnormally large grains (ALGs) can all be
formed due to the presence of stored energy gradients and subsequent annealing in Ni-superalloys
[143, 166-169] (See Figure 15). The formation of ALGs is of particular interest, as it can severely
affect mechanical performance by degrading structural integrity and serving as initiation sites for
failure [170, 171]. Previous research has found that the formation mechanisms of ALGs can be
attributed to two factors: (1) limited number of nucleation sites available for recrystallization and
(2) gradient distribution of stored energy across grain boundaries [166]. Therefore, there is an
opportunity to increase control of HNM design by leveraging the stress gradients to influence
structural formation.

29

Figure 15: Illustration of heterogeneous structural formation in NT Inconel 725 films at 3, 5, and 8 hours of heat
treatment. Depending on the length of the treatment, carbides, rafted structures, δ-phase precipitates, and ALGs can
form, due to an intrinsic stored energy gradient [143].

2.4.2.2.1. Residual Stresses and stored energy gradients
Sputtering can introduce complicated intrinsic stress profiles at interfaces between the film and
substrate due to metastable growth processes [172], lattice mismatch between materials [173], or gradient
stresses throughout the film thickness [174, 175]. Gradients in stress profiles can be introduced by varying
deposition conditions, self-organization phenomena such as competitive grain growth and diffusion along
grain boundaries, postdeposition mechanical and thermal loads, or effects from the surrounding
environment upon chamber evacuation [176]. When a material is annealed, these stress gradients can
facilitate heterogeneous structural formations, as seen in several sputtering systems [39, 41, 143]. For
example, in the proof-of-principle work by Bahena et al., variations in stress throughout the film thickness
were promoted by the sputtering parameters used during film synthesis. The stress profile was mapped
using grain orientation spreads (GOS), as seen in Figure 16. The GOS map is a semi-qualitative
representation of the stored energy landscape throughout the film thickness, examining deviations in local
grain misorientations [166, 167, 177]. Grains with larger orientation spreads tend to have higher stored
energy [178]. It can be observed in the figure that a GOS gradient exists, with larger GOS toward the bottom
of the film, suggesting the presence of a stored energy or stress gradient profile throughout the film
thickness.
30

Figure 16: Grain orientation spread (GOS) map and corresponding grain distribution plots, highlighting a gradient in
GOS [143].

Understandably, intrinsic film stresses are often viewed as a boogeyman to functional
coatings, as they can hinder film adhesion [179-181] or cause total film failure via cracking due to
tensile stresses [182, 183] or peeling, buckling, or blistering due to compressive stresses [184-
187]. However, controlling the stress profile in the films by managing deposition conditions can
have a significant positive impact on functional properties, ranging from conductivity [188] to
magnetic capabilities [189, 190], and physical properties, such as hardness, toughness, oxidation
resistance, wear behavior, adhesion, and durability [176]. One avenue of influencing the stress
profile includes changing the lattice mismatch between substrate and film material. Previous
studies have found stress to be highest at interfaces between substrate and film material, due to
growth processes, lattice misfit [174], or differences in coefficient of thermal expansion (CTE)
31

[191]. Depositing a material on substrates with similar lattice parameters or CTE may be useful in
limiting the interfacial stress between the two components.
Another method of influencing the stress state is by introducing compositional variations to
the Ni-superalloys. Previous work has examined the effect of alloying via co-sputtering on residual
stress evolution in binary nanocrystalline films [192-197], with the results being a bit of a mixed
bag dependent on element miscibility and mobility, as well as grain boundary characteristics [165].
To the author’s knowledge, there are no studies examining the further alloying of Ni-superalloys
to influence the stress state, although the addition of highly mobile, insoluble elements in the Ni
matrix, such as Zr or Hf, may play a role in the stability of GBs and precipitation behavior [198].
Together, each of these characteristics should be examined further to allow for the tailoring of film
stress, thereby increasing the ability to influence heterogeneous microstructural formation.

2.5. Summary
Nanostructured materials continue to be an enticing field of study due to their
multidisciplinary potential, particularly as high strength materials due to the Hall-Petch effect. As
a result, significant work in recent years has focused on improving their limitations, namely
instability at elevated temperatures and brittle mechanical behavior. Recent work on binary and
ternary alloy nanostructured materials indicate that the incorporation of multiple alloying elements
may alleviate poor thermal stability, paving the way for the study of multi-component material
solutions. Indeed, compositional complexity is being explored as a mechanism for improving the
performance of nanostructured materials, as many of the characteristics of MPEAs, such as lattice
distortion, sluggish diffusion, “cocktail”, and high entropy effects, are believed to aid in the
stabilization of grains. Simultaneously, microstructural complexity in the as sputtered or annealed
state, such as the formation of nanotwins or heterogeneous structures, respectively, can further
enhance the mechanical and physical performance of nanostructured materials. Magnetron
sputtering, a PVD technique, is uniquely equipped to address these open scientific problems, as it
has been proven as a useful mechanism for producing films with nanosized features,
nanostructured alloys, and microstructurally complex materials, while also being capable of
synthesizing compositionally or microstructurally gradient materials, allowing for the examination
of multiple samples in the same sputtering run. Thus, this work seeks to employ magnetron
32

sputtering to synthesize nanostructured films with either compositional or microstructural
complexity, to further improve upon their multifunctionality and accelerate their deployment.

33

3. Chapter 3: Experimental Methods

3.1. Magnetron Sputtering
Magnetron sputtering, a physical vapor deposition (PVD) technique, is a versatile synthesis
method that is used to produce films ranging anywhere from a few nanometers to several microns
thick, and features a wide range of tunable conditions [199]. These conditions include the ability
to deposit nearly any single element, alloy, or ceramic material, as well as tailorable deposition
parameters such as working pressure, working gas, substrate temperature, and target power [19].
A schematic of the magnetron sputtering process is provided in Figure 17. In this process, the
sputtering chamber is filled with an inert gas, which is then converted into high-energy ionized
particles with the introduction of a DC bias. These particles then bombard the surface of a
sacrificial material target (cathode), causing the atoms of that target to be ejected, thus creating a
vapor within the chamber. As the vapor condenses, the material deposits and coats a substrate
(anode) layer-by-layer, resulting in the formation of a film adhered to the substrate.

Figure 17: Schematic of sputtering chamber [200].
34

The configuration of the magnetron sputtering chamber is quite customizable. The
incorporation of heating and cooling stages, reactive gas injection, and stage biasing can all play a
role in film formation, as these techniques have been shown to influence twin thickness [145],
amorphization [23], and film morphology [201], respectively. The use of co-sputtering
arrangements, in which multiple cathodes are used to deposit discrete materials from each cathode,
can enhance control over material stoichiometry and promotes the opportunity to explore wider
composition spaces [23]. Furthermore, the use of shutters and masking can allow for increased
throughput in experimentation, as multiple samples with varying properties can be synthesized in
a single sputtering run. A schematic of a co-sputtering arrangement with shuttering and masking
is included in Figure 18.

35

Figure 18: Schematic of co-sputtering arrangement, including the usage of three sources, masking, and a shutter to
produce multiple samples in a single sputtering run.

3.2. Residual stresses and profilometry
As mentioned in Section 2.4.2.2.1, residual stresses can be introduced either intrinsically or
extrinsically during the film deposition process [176]. To measure the global stress present in the
36

films, profilometry can be employed to measure the radius of curvature of the film-substrate
system, which is directly related to the stress by Stoney’s Equation (Equation 8) [202]:
𝜎 𝑠𝑡𝑜𝑛𝑒𝑦 =
−𝐸 𝑠 𝑡 𝑠 2
6𝑡 𝑓 ( 1−𝜐 𝑠 ) 𝑅 (8)
Where σstoney is the residual stress of the film, Es is the elastic modulus of the substrate, ts is the
thickness of the substrate, tf is the thickness of the film, υs is Poisson’s ratio of the substrate, and
R is the radius of curvature of the film-substrate system. To measure the radius of curvature, a
stylus profilometer is utilized, where a 20 nm diameter diamond stylus tip contacts and moves
along the surface of a material laterally, measuring the local vertical displacement of the stylus, as
shown in Figure 19 [203]. A profile of vertical displacement along the sample surface can be
acquired before and after deposition to determine radius of curvature using Equation 9:
𝑅 =
𝐿 2
8𝛿 𝑚𝑎𝑥 (9)
Where L is the length of the coating along the substrate face and δmax is the maximum deflection.
Once the change in R of the substrate due to deposition is measured, the global residual stress state
can be determined. Profilometry is also useful for determining sputtering rates, which can then be
directly linked to composition during co-sputtering. In this work, profilometry was performed
using an AMBiOS XP-2 Profilometer.

37

Figure 19: Profile data acquisition by a stylus-type profilometer [203].

3.3. Heat Treatments
Heat treatments refer to the heating (and cooling) of a solid metal or metal alloy to obtain
specific desired conditions or properties. Different treatments include annealing, normalizing,
stress relieving, surface hardening, tempering, and quenching. Each of these treatments can
individually alter the properties of the material, or they can be combined in multi-step processes
[204]. For example, the heat treatment of Inconel 725 involves an initial solution anneal, quench,
age hardening, and recrystallization process. A graph for the standard dual-aging treatment is
included in Figure 20.
38

Figure 20: Temperature v. time graph of Inconel 725 standard age hardening treatment.

Multiple heat treatments were leveraged for the materials studied in this work. When
examining the formation of heterogeneous nanodomains in Inconel 725, a modified version of the
standard Inconel 725 aging treatment [205] was applied. The annealing procedure used in this
work differs slightly from the standard age hardening treatment of Inconel 725 in two ways [206]:
First, the initial solution anneal can be skipped as sputtering has been shown to force solid
solutions. Second, the end treatment was also not performed as it would cause complete
recrystallization of the material. Since the interest in this work is to examine metastable structural
formation at different treatment intervals, the complete recrystallization of the material is
undesirable, thus the second leg of the dual-aging treatment was not implemented. A graph of the
modified heat treatment used in this work is included in Figure 21. Samples were heated to 730⁰C
for 5 hours and then were allowed to cool to RT at a rate of 5⁰C/min. After cooling was completed,
samples were removed from the furnace and subsequently kept in a desiccator until
characterization.
39

Figure 21: Temperature v. time graph of Inconel 725 age hardening treatment used in this work. The initial solution
anneal and end phase portions of the standard treatment were skipped.

For the work examining the effect of dopant elements on microstructural formation in
additively manufactured Inconel 718, the standard Inconel 718 dual-aging heat treatment was
utilized, as seen in Figure 22 [207]. The initial solution anneal was again skipped as sputtering
forces a solid solution. Samples were heated to 718°C for 8 hours, cooled at a rate of 55°C/hour to
620°C and treated at that temperature for 8 hours. The sample is then furnace cooled to room
temperature at a rate of 5°C/min before being removed from the furnace. All the heat treatments
in this work were performed in a GSL1100X tube furnace combined with a getter pump under low
vacuum (~ 10
-5
Pa).

40

Figure 22: Temperature v. time graph of Inconel 718 double aging heat treatment leveraged in this work. The initial
solution anneal was skipped, as sputtering forces a solid solution.

3.4. Microstructural Characterization
3.4.1. X-ray Diffraction
X-ray diffraction (XRD) is considered to be at the intersection of the physics of x-rays and
the geometry of crystals [208]. Using this technique, crystallographic orientation (texture) and
material phases can be identified in a non-destructive manner. XRD utilizes x-rays, which upon
scattering, results in the production of diffraction peaks that correspond to the lattice plane spacing
in the sample. This spectrum represents the scattered intensity as a function of 2θ, where the
direction of the scattered x-rays is determined by the wavelength of the incident wave and the
atomic arrangement of the sample [208, 209]. Bragg’s law (Equation 10) describes this diffraction
from the material:
𝑛𝜆 = 2𝑑𝑠𝑖𝑛𝜃 (10)
Where n is a positive integer, λ is the incident wavelength, d is the interplanar spacing of the lattice,
and θ is the incidence angle between the atoms of the sample and the incident wave. The
relationship is satisfied when there is constructive interference between the incident wave and
sample atoms. An example of XRD spectra is included in Figure 23. In this work, XRD
41

measurements are acquired using a Rigaku Ultima IV X-Ray Diffractometer or Bruker D8
Advance Diffractometer.
Figure 23: Example XRD spectra of various CuAl and CuNi films synthesized using different sputtering parameters
[144].

3.4.2. Scanning Electron Microscopy and Energy-Dispersive X-ray Spectroscopy
Scanning electron microscopy (SEM) allows for the examination, imaging, and analysis of
the microstructure, topology, and chemical composition of a material. In SEM, a filament or field
emission gun generates an electron beam, which then scans over the surface of a sample [210]. As
a result, both elastic and inelastic interactions between the electron beam and the sample surface
occur. Figure 24 illustrates the interaction volume of the incident electron beam and the sample
surface, resulting in multiple reactions. In elastic collisions, the energy of the electrons is
conserved, resulting in colliding electrons being reflected at high angles. These electrons are
known as back-scattered electrons, whose signal can be used to decipher differences in chemical
42

composition and phases along a sample surface, providing brighter or darker regions for different
chemical compositions in the resulting image [211]. When the interaction between the electron
beam and sample surface is inelastic, secondary electrons and characteristic x-rays are produced.
Secondary electrons can describe topological differences along the surface of the sample, including
surface texture and roughness [211, 212].
Figure 24: Illustration of several signals generated by the electron beam–specimen interaction in the scanning electron
microscope and the regions from which the signals can be detected [213].

X-ray signals are produced when non-valence electrons are disturbed and displaced
because of inelastic collisions with incident electrons [211, 212]. The characteristic x-rays can then
43

have their associated energies identified and quantified in a process known as energy dispersive x-
ray spectroscopy (EDS), which can be leveraged to provide semi-quantitative elemental
composition information. EDS mapping can be utilized to identify elemental segregation,
compositional gradients, or any heterogeneity in a material’s composition in a given area. In this
work, both SEM and EDS were conducted using a FEI Nova NanoSEM 450 and FEI Helios G4
P-FIB.

3.4.3. Electron Back Scatter Diffraction and Transmission Kikuchi Diffraction
Electron back scatter diffraction (EBSD) is a scanning electron microscope accessory that
allows for the analysis, quantification, and visualization of a material’s microstructure. When tilted
to an angle of ~70⁰, the interaction between the sample and the electron beam results in electron
scattering. Certain electrons will satisfy Bragg’s law (Equation 10) of a specific crystallographic
plane, thus generating Kikuchi diffraction patterns [214]. The Kikuchi patterns can then be
acquired by a detector to create an EBSD map, composed of grains and boundaries notated by their
orientation, as seen in Figure 25. This information provides a complete picture of grain orientation,
boundaries, and sizes.

44

Figure 25: Top surface EBSD IPF maps showing grain evolution of as-sputtered (A) Cu2Al-A, (B) Cu2Al-B, (C)
Cu10Ni-A, and (D) Cu10Ni-B after heat treatments performed at 200°C, 400°C, and 600°C. Dashed boxes highlight
instances of significant grain growth, note the changes in scale bar. The IPF triangle is shown to the right of the scans
[144].

It should be noted that the spatial resolution of EBSD is limited to a maximum of 20 nm
[214-216], making routine analysis of truly nanostructured materials quite cumbersome.
Therefore, orientation mapping techniques with higher spatial resolution are required. One such
technique is Transmission Kikuchi Diffraction (TKD), which is also sometimes referred to as
transmission-EBSD (t-EBSD). For TKD analysis, the sample must be electron transparent and
mounted horizontally or backtilted away from the EBSD detector, positioned level with or above
the top plane of the EBSD detector. The difference in geometry from traditional EBSD positioning
results in the diffraction pattern originating from the bottom surface of the sample with a smaller
diffraction source volume [217], thus allowing for a tenfold improvement in spatial resolution to
45

~2 nm [218]. An example of a TKD map acquired from nanocrystalline Cu can be found in Figure
26. EBSD and TKD analysis in this work were performed by using an Oxford Symmetry detector
in a FEI Helios G4 P-FIB.
Figure 26: TKD results from the nanocrystalline Cu sample. The scale bar in all images is 500 nm. (a) DF image
collected using forescatter detectors. (b) ODF image highlighting orientation variations. (c) TKD pattern quality map
of the same area. (d) TKD orientation map (inverse pole figure z-direction coloring), with high-angle boundaries in
black, low-angle boundaries in grey and coincident site lattice boundaries in colors. White arrows mark locations
showing evidence of nanocrystalline grain growth [219].

3.4.4. Focused Ion Beam
Focused Ion Beam (FIB) is a useful tool for examining cross sections of samples or
preparing samples for other characterization techniques. The FIB system is a dual beam
configuration that combines the capabilities of an SEM in one column and an ion beam in another.
The traditional ion beam column utilizes Ga
+
ions to bombard and mill specimens, thus resulting
in the emission of back-scattered ions, radiation, and ion induced secondary electrons, which are
collected for imaging purposes. A relatively new type of FIB technique is the plasma focused ion
beam (PFIB) which incorporates a Xe
+
plasma ion source, which can improve high throughput
milling rates and reduce surface damage by avoiding Ga
+
implantation [220].
46

Combining the PFIB with a micromanipulator and gas injection system yields the ability to prepare
samples for transmission electron microscopy (TEM) and TKD. In TEM, samples must be less
than 100 nm thick for adequate electron transparency [221]. In the PFIB, a lamella is extracted
from the as-sputtered film by milling a region of interest and transferring it to a TEM lift-out grid.
Once the sample is properly transferred, it is milled further to thin the sample to electron
transparency. Figure 27 provides a step-by-step layout of how this process is accomplished.
Sample preparation for TEM was conducted using a FEI Helios G4 P-FIB.
Figure 27: The steps involved in FIB sectioning showing the preparation of the chosen area (a), cutting the side
trenches and preparing for lift-out (b), the micromanipulator is attached to the sample for lift-out (c) and the sample
is attached to a copper TEM grid (d) [222].

47

3.4.5. Transmission Electron Microscopy
In transmission electron microscopy (TEM), a high energy electron beam generated by a
field emission gun and then made parallel through a series of condenser lenses is used to study
sufficiently thin (<100 nm thick) samples [223]. This technique allows for the observation and
analysis of nanoscale structural features. When the electrons encounter the sample, different types
of collisions occur (elastic or inelastic), resulting in transmitted electrons that can then be collected
to produce microstructural information. In elastic interactions, the transmitted electrons conserve
their energy and produce diffraction patterns. In inelastic interactions, the electrons lose their
energy either due to absorption or scattering. In this case, the intensity of the beam is affected,
resulting in the contrast of microstructural features. Thus, the signal from inelastic interactions is
useful for imaging. To switch between viewing the diffraction pattern or imaging the sample, the
strength of the intermediate lens can be adjusted. To see diffraction patterns, the intermediate lens
is adjusted to focus on the back focal plane of the objective lens. In the imaging mode, the
intermediate lens is adjusted to focus on the object plane of the objective lens [224]. The main
TEM operation modes are visualized in Figure 28 and can be differentiated as follows:

Bright Field (BF): Bright field imaging is the conventional TEM mode. In this setting, the aperture
is centered around the transmitted beam, thus blocking all diffracted beams from contributing to
image formation. Bright field images exhibit contrast due to local variations in microstructure.

Dark Field (DF): In dark field mode, the aperture is positioned around one of the diffracted beams
while blocking all others. This is a useful technique for analyzing grain size, as only grains that
diffract strongly in the selected direction are visible in the image. Thus, dark field mode can clearly
display grain morphology.

Selected Area Electron Diffraction (SAED): The most common diffraction mode in TEM is
SAED, in which an aperture limiting the area contributing to the diffraction pattern is inserted into
the first immediate image plane. In this mode, the shape and distances of the patterns can be used
to determine crystal structure, lattice parameters, orientation, defects, and interfaces in a sample.

48

High Resolution (HR) Imaging: High resolution TEM imaging can be used to acquire atomic
resolution micrographs where lattices can be resolved. To conduct this type of imaging, the angle
of the electron beam is tilted to combine the central and some diffracted beams.
Figure 28: Illustration of TEM aperture and lens configuration for different modes: (a) bright field, (b) dark field, and
(c) SAED with corresponding image results of Hf-Ti multilayers (d-f) [225].

3.4.6. Scanning Transmission Electron Microscopy
Unlike conventional TEM modes, where the entire sample is illuminated simultaneously,
scanning transmission electron microscopy (STEM) scans the specimen in a point-by-point raster
with a small electron probe [223]. The electrons that are transmitted through the sample in this
manner can then be collected by both a bright field and high angle annular dark field (HAADF)
detector. The bright field detector collects electrons transmitted parallel to the beam, yielding
images formed via diffraction contrast that is better in comparison to bright field TEM
49

micrographs. The HAADF detector collects high angle incoherent scattered electrons, which forms
images with compositional contrast. The interaction between the electron beam and the sample
also produces x-rays, which, similarly to the SEM, can be collected via EDS to analyze
compositional data and map compositional variation in the sample with resolution near the spot
size. An example of STEM coupled with EDS analysis is provided in Figure 29. TEM, STEM, and
EDS analysis in this work were performed using a JEOL JEM-2100F.
Figure 29: (A) BF-STEM image of heterogenous precipitation and microstructural behavior in magnetron sputtered
Inconel 725 after 5 hours of heat treatment. SAED pattern provided inset confirms the presence of δ precipitates. (B)
EDS maps of Ni, Cr, Ti, and Nb highlighting location of different precipitates where white scale bars are 1 µm. [143].

3.4.7. Secondary Ion Mass Spectrometry (SIMS) and NanoSIMS
Secondary Ion Mass Spectrometry (SIMS) involves the bombardment of a material surface
with a primary ion beam, resulting in the ablation and sputtering of the top few atomic layers of
the sample surface, generating secondary ions of both polarities. These secondary ions can then be
collected and analyzed using a mass spectrometer to generate mass-resolved 1D depth profiles, 2D
images, and even 3D chemical mapping [226]. This technique features extreme sensitivity, able to
detect the presence of elements in ranges of parts per million (ppm) to parts per billion (ppb) [227].
In the last 30 years, the SIMS technique has been improved to feature very high spatial resolution
(down to 50 nm) and high collection efficiency by leveraging very small beam currents. Coined
NanoSIMS, this improved method allows for the collection of up to seven ionic species
50

simultaneously, allowing for more precise isotope ratio measurements with enhanced resolution
[228]. Chemical imaging of elements in trace amounts is of particular interest in metallurgy, as
even very small ratios of contaminants can negatively affect material properties. For example, in
Figure 30, it can be seen how S segregates to Al2O3 sites in an additively manufactured Inconel
625 sample, leading to creep embrittlement despite the S making up <100 ppm of the entire sample
composition. In this work, NanoSIMS experiments were performed at the California Institute of
Technology using a CAMECA NanoSIMS 50L.

Figure 30: NanoSIMS maps of Inconel 625 showing how S segregates to Al 2O 3 sites, leading to embrittlement [207].

3.5. Mechanical Characterization
3.5.1. Vickers micro-indentation
Mechanical indentation is a useful technique for evaluating the micro- and macro-scale
deformation behavior of materials. In indentation, an indenter tip of known geometry is pressed
51

into a sample at a known force. The hardness of the material can then be determined by dividing
the force by the indenter surface area, as seen in Equation 11:
𝐻 = 1 ∗ 10
3
∗
𝑃 𝐴 𝑠 = 2 ∗ 10
3
∗
𝑃𝑠𝑖𝑛 (
𝛼 2
)
𝑑 2
(11)
Where P is the force in grams, As is the contact area, α is the face angle of the indenter and d is the
mean diagonal length of the indent. Many different indentation techniques exist, including
Rockwell, Knoop, and Vickers indentation. In the Vickers micro-indentation method, a square-
based pyramidal diamond indenter is leveraged [229] at force values between 10g and 1000g. It
should be noted that the same tip is used across the entire force range, as the test is considered
force independent. For Vickers hardness testing, the face angle of the indenter is 136°, allowing
for the reduction of Equation 11 to Equation 12:
𝐻𝑉 = 1854.4 ∗
𝑃 𝑑 2
(12)
Where HV is the Vickers hardness, P is the force in grams, and d is the mean diagonal length of
the indent. The shape of the resulting indent can then provide information about the deformation
behavior of the material [230]. Figure 31 provides top surface SEM micrographs of Vickers indents
and corresponding FIB cross-sectional images, showing how the shape of the Vickers indent
changes with material type. In this work, a LECO-LM100 Vickers micro-indenter was leveraged
to perform Vickers indentation testing.

52

Figure 31: (a) Representative SEM surface micrographs of Vickers indents and (b) FIB cross-sectional micrographs
underneath the indents in the Ag foils containing (1) 10%, (2) 40%, and (3) 100% NT grains [230].
53

3.5.2. Nanoindentation
In hardness testing, an indenter of known geometry is pressed into the surface of a material
under a fixed load. The depth of the penetrated area can then be used to measure the resistance of
the material to damage. However, difficulty arises when attempting to perform this type of test as
the contact scale is greatly reduced, such as in the case of thin films and coatings. Continuously
recording the load and indenter displacement can resolve this issue, as mechanical properties can
then be probed at shallow contact depths. Typically, these depths are in the nanometer range, hence
the term nanoindentation. This testing technique allows for precise control of either the load or
displacement during the test. At very low loads, mechanical characterization of coatings and
surface features can be performed with minimal substrate contribution to the results [231].
Simultaneously, an array of indents can be performed that yield statistically significant
results about the mechanical properties of the material. Typically, this technique is used to
determine the hardness and reduced elastic modulus of a material, which can be found by using
the resultant data found in a load-displacement curve (an example of which is included in Figure
32). The combination of the elastic equations of contact and the unloading data in the curve can
thus be used to calculate the hardness and reduced elastic modulus. The equations for hardness
and reduced elastic modulus, respectively, are as follows based on the Oliver-Pharr method [232]:
𝐻 =
𝑃 𝑚𝑎𝑥 𝐴 (13)
𝐸 𝑅 =
𝑑𝑃
𝑑 ℎ
1
2
√ 𝜋 √ 𝐴 (14)
Where H is the hardness, Pmax is the maximum applied load, A is the contact area, Er is the reduced
elastic modulus, and
𝑑𝑃
𝑑 ℎ
is the slope of the elastic unloading curve. In this work, nanoindentation
was performed using a Hysitron Triboindenter with a 50 nm Berkovich tip using a force-controlled,
constant loading rate load function.

54

Figure 32: Representative nanoindentation load-displacement curve.

55

4. Chapter 4: Phase transition zones in compositionally complex alloys
A version of the following work is published as a journal article titled Phase transition zones in
compositionally complex alloy films influenced by Al and Ti content in Surface and Coatings
Technology, 424, 127651, (2021) DOI: 10.1016/j.surfcoat.2021.127651.

4.1. Introduction
The study of multi-principal element alloys (MPEAs), a field including high entropy alloys
(HEAs) and compositionally complex alloys (CCAs), has been an exciting topic of novel alloy
development. MPEAs feature a variety of desirable properties, including high hardness and
strength [67, 233-235], fatigue resistance [236, 237], fracture toughness [79], biocompatibility
[74], resistance to oxidation [68, 69], wear [64-67], and corrosion [70-73], and have been shown
to exhibit unique electrical and magnetic properties [75-77, 238]. To date, the emphasis of the field
has focused on the development of HEAs, however, CCAs present the opportunity to explore a
larger composition space due to a more flexible alloy definition. While both HEAs and CCAs are
composed of four or more alloying elements between 5 and 35 at.% of the total composition, such
that there is no base element, HEAs are commonly equiatomic and the term “HEA” is typically
used when either the configurational entropy or the objective of producing single-phase solid
solutions is important [81]. In comparison, CCAs do not need to be equiatomic and can possess
crystal structures other than single-phase solid solutions [112]. Traditional synthesis methods to
fabricate bulk CCAs include spark plasma sintering [239], mechanical alloying [240] and arc
melting [241], though such techniques have demonstrated a lack of control over grain size, global
composition and elemental distribution [42], and possess limitations in high-throughput screening
within the vast composition space of CCAs [242].
In contrast, techniques such as physical vapor deposition (PVD) present a high-throughput
alternative for CCA synthesis, allowing for the exploration of multiple compositions, and/or
compositional gradients on the same substrate [98, 113, 243]. Current experimental works have
indicated that CCA films and coatings exhibit comparable mechanical and physical properties to
their bulk counterparts, which range from high hardness to unique magnetic properties [244-250].
However, differences in growth mechanisms, grain size, process temperature, and rapid diffusion
during synthesis can contribute to discrepancies in phase formation between bulk and thin film
56

studies [201]. For example, CCA film synthesis via PVD features rapid cooling rates compared to
bulk CCA synthesis methods [23], which can restrict diffusion and minimize the nucleation and
growth of intermetallic compounds, ultimately inhibiting phase separation [251]. Additionally, the
influence of alloying elements, such as Al [68, 98, 252, 253], Cu [254-256], Ni [256], V [64], and
Ti [65, 97], have been documented in bulk arrangements, but their impact on thin film morphology
has yet to be thoroughly explored.
To date, the preferred processing method for deposited MPEA films has been magnetron
sputtering [23, 199, 257] with a focus primarily on nitride and oxide-films [246-248, 250, 257-
261]. The wide range of tunable conditions [199] in sputtering include the ability to deposit nearly
any single element, alloy, or ceramic material, as well as tailorable deposition parameters such as
working pressure, working gas, and target power [19]. Sputtering from a single MPEA target with
a set composition has been employed in many systems [96, 99, 201, 244, 249, 262-267]; however,
stoichiometry control can be further enhanced by leveraging co-sputtering assemblies and
depositing from multiple targets. This technique allows for the ability to change the deposition rate
of individual target materials and thus contributes to compositional variation and microstructural
development [23]. Additionally, co-sputtering enables individual elements within the MPEA
arrangement to be isolated, granting the opportunity to focus on their atomic characteristics
including atomic size, crystallography, and valence electron structure, all which contribute to the
phase formation within these materials. In general, experimental studies that have varied elemental
compositions within MPEA systems treat alloy synthesis as a pseudo-binary arrangement dictated
by the Hume-Rothery rules [268] with a single “large” element and several “small” elements.
Herein, “large” element refers to those with an atomic radius greater than 140 pm, while the
remaining “small” elements are usually transition metals with similar atomic radii of
approximately 130 pm or less. In those cases, the “large” element typically drives phase formation
mechanisms, as it greatly contributes to atomic size differences and lattice distortion effects [23].
However, both the synthesis method (as outlined previously) and electron structure of the “large”
element cause inconsistencies in phase formation across studies. Furthermore, studies beyond one
“large” element or the influence of the smaller elements have been limited specifically within the
context of phase formation.
57

In this study, magnetron co-sputtering techniques were employed to vary the composition of
two “large” elements (Al and Ti) within the AlCrFeNiTi and AlCoFeNiTi CCA families to
examine their influence on phase morphology transitions. Additionally, Cr was substituted with
similarly sized, but structurally dissimilar, Co to observe the effect of the “small” elements on the
overall microstructure. Respective compositions are maintained between 5 and 35 at.% in
accordance with the defined CCA range. The resultant microstructures were characterized using
scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), and X-ray
diffraction (XRD) techniques to determine crystallite size and critical alloying element
composition thresholds where crystallographic transitions could occur. The mechanical properties,
namely hardness and moduli, were examined using nanoindentation to correlate structural trends
to compositional variations. Overall, this study highlights phase transitions in sputtered materials
while simultaneously exploring the contributions of both “large” and “small” elements in
compositionally complex arrangements, which can serve as model alloy systems for future CCA
design.

4.2. Materials & methods
Samples were synthesized using direct current (DC) magnetron sputtering from high purity,
single element Al (99.99%) and Ti (99.995%) targets, as well as vacuum arc melted ternary alloy
CrFeNi (99.9%) and CoFeNi (99.9%) targets (Plasmaterials, Inc.). A three-source sputtering
configuration was used to co-sputter both of the single element targets with one of the ternary alloy
targets onto 50 mm Si (100) substrates to produce ~1 μm thick AlCrFeNiTi and AlCoFeNiTi films.
The working distance for all targets was 13 cm. Each substrate was separated into quadrants to
synthesize multiple compositional arrangements simultaneously with the assistance of masking
and a pneumatic shutter (see Figure 18 in Section 3.1). Due to the orientation of the setup, two
distinct sputtering runs can be completed per substrate, yielding four unique compositions. These
sputtering conditions are included in Tables 17 and 18 in the Appendix (Section B). Sputtering
powers were selected such that the nominal expected composition values for each alloying element
were within the necessary defined range for CCAs. The resulting sample thicknesses were
measured using an AMBiOS XP-2 profilometer. It should be noted that the nomenclature for the
samples presented in this study is separated into “systems” and individual sample names. The
58

systems are as follows: within the AlCrFeNiTi family, system 1 (varied Al) and system 2 (varied
Ti); within the AlCoFeNiTi family, system 3 (varied Al) and system 4 (varied Ti). Each individual
sample is labeled with the system number, the composition of the varied element in at.%, and the
sputtering quadrant region on the substrate i.e., either top (T) or bottom (B). For example, S1-5Al-
T constitutes the sample within system 1 with 5 at.% Al from the top quadrant, while S2-32Ti-B
corresponds to a sample within system 2 with a 32 at.% Ti from the bottom quadrant.
The elemental compositions of each sample were characterized by scanning electron
microscopy/energy dispersive X-ray spectroscopy (SEM/EDS) (FEI Helios G4 P-FIB) at 15 kV.
Top-surface micrographs were acquired via SEM using a beam current of 50 pA and an
accelerating voltage of 10 kV. Grazing incidence X-ray diffraction (GIXRD) with Cu Kα radiation
and a grazing angle of 2° was employed. Scans were conducted over a 2θ range from 20° to 120°
or to 140° depending on the system of samples, with a step size of 0.05°/sec and a sampling rate
of 1°/min using a Rigaku Ultima IV Diffractometer. Average crystallite size was determined from
the full-width half maximum (FWHM) of the main diffraction peaks using Sherrer’s Equation
[269], presented in Equation 15:
𝑡 =
0.9𝜆 𝐵𝑐𝑜𝑠 𝜃 𝐵 (15)
Where t is the crystallite size, λ is the X-ray wavelength, B is the FWHM of the peak, and θB is the
Bragg angle. Average crystallite sizes for all samples are included in Table 2. In addition to
microstructural characterization, nanoindentation was performed in a Hysitron Triboindenter with
a 50 nm Berkovich tip using a force-controlled, constant loading rate load function. A set of 100
indents, positioned 20 μm apart in the center of each sample quadrant, were measured to derive
hardness and reduced elastic moduli values. The equation for reduced modulus is provided in
Equation 14 in Section 3.5.2. Representative load-displacement curves are included in the
Appendix (Section B., Figures 54 and 55).

59

Table 2. Crystallinity and average crystallite size of samples in all systems.
AlCrFeNiTi
System 1 – Varied Al System 2 – Varied Ti
Sample Crystallinity
Avg.
Crystallite
Size (nm)
Sample Crystallinity
Avg.
Crystallite
Size (nm)
S1-7Al-T

Amorphous 1.66 ± 0.01 S2-5Ti-T

Disordered BCC 6.48 ± 0.06
S1-7Al-B

Amorphous 1.65 ± 0.01 S2-5Ti-B

Ordered BCC 9.37 ± 0.03
S1-15Al-T

Amorphous 1.63 ± 0.01 S2-7Ti-T

Amorphous 1.71 ± 0.01
S1-15Al-B

Amorphous 1.66 ± 0.01 S2-7Ti-B

Disordered BCC 7.11 ± 0.05
S1-33Al-T

Amorphous 1.66 ± 0.01 S2-8Ti-T

Amorphous 1.88 ± 0.00
S1-33Al-B

Amorphous 1.60 ± 0.01 S2-8Ti-B

Disordered BCC 2.02 ± 0.01
S2-13Ti-T

Amorphous 1.63 ± 0.01
S2-13Ti-B

Amorphous 1.67 ± 0.01
S2-32Ti-T

Amorphous 1.57 ± 0.01
S2-32Ti-B

Amorphous 1.58 ± 0.01
AlCoFeNiTi
System 3 – Varied Al System 4 – Varied Ti
Sample Crystallinity
Avg.
Crystallite
Size (nm)
Sample Crystallinity
Avg.
Crystallite
Size (nm)
S3-5Al-T

Disordered BCC 3.27 ± 0.03 S4-5Ti-T

Mixed 5.07 ± 0.04
S3-5Al-B

Amorphous 1.68 ± 0.00 S4-5Ti-B

Ordered BCC 9.10 ± 0.06
S3-10Al-T

Mixed 11.21 ± 0.05 S4-9Ti-T

Mixed 4.54 ± 0.04
S3-10Al-B

Amorphous 1.43 ± 0.01 S4-9Ti-B

Ordered BCC 9.97 ± 0.04
S3-30Al-T

Ordered cubic 12.68 ± 0.16 S4-35Ti-T

Amorphous 1.29 ± 0.00
S3-30Al-B

Ordered cubic 10.41 ± 0.08 S4-35Ti-B

Amorphous 1.91 ± 0.02
*Note: Crystallite sizes for “amorphous” samples are estimates for comparison to the ordered and
“mixed” phase samples. Samples labeled as “amorphous” from XRD data can contain small
crystallites.

4.3. Results & discussion
As previously mentioned, there is limited research of CCA arrangements beyond those which
are comprised of a single “large” element amongst several “small” elements largely due to
synthesis control limitations [242]. However, a versatile synthesis technique like magnetron
sputtering affords the ability to isolate each individual element (“large” or “small”), while
elucidating on how atomic characteristics contribute to phase formation. In this study, sputtering
allowed for the synthesis of four unique compositions per substrate, as outlined in the Materials &
methods section (Section 4.2). Alterations in composition were introduced depending on which
60

element was varied (Al or Ti) and the substrate quadrant position of the sample (either top or
bottom). These compositional values are presented in Tables 3 and 4. As such, the role of having
multiple “large” elements in a CCA arrangement is explored by varying the Al and Ti content in
the AlCrFeNiTi (section 4.3.1) and AlCoFeNiTi (section 4.3.2) families, while simultaneously
exploring the influence of “small” elements i.e., Cr vs. Co. Section 4.3.3 further explores the effect
of composition on mechanical properties by using nanoindentation techniques.

Table 3: Elemental composition derived from EDS data for systems 1 and 2 in the AlCrFeNiTi family.
AlCrFeNiTi
System Sample Al (at.%) Ti (at.%) Cr (at.%) Fe (at.%) Ni (at.%)
1
S1-7Al-T 7.05 12.81 26.10 26.58 27.47
S1-7Al-B 7.64 19.31 23.90 24.19 24.89
S1-15Al-T 15.12 18.76 21.62 21.94 22.57
S1-15Al-B 15.08 12.68 23.86 23.84 24.54
S1-33Al-T 32.42 14.66 17.32 17.45 18.15
S1-33Al-B 32.75 10.47 18.42 18.74 19.62
2
S2-5Ti-T 16.60 5.00 25.71 25.66 27.04
S2-5Ti-B 26.58 5.17 22.33 22.56 23.36
S2-7Ti-T 17.24 6.32 25.37 24.96 26.11
S2-7Ti-B 26.52 6.73 21.80 22.10 22.86
S2-8Ti-T 14.45 7.66 25.67 25.58 26.63
S2-8Ti-B 23.05 8.12 22.50 22.48 23.86
S2-13Ti-T 23.54 12.69 20.95 21.01 21.81
S2-13Ti-B 15.60 12.08 23.79 23.86 24.66
S2-32Ti-T 19.85 32.12 15.76 15.76 16.51
S2-32Ti-B 13.34 31.74 18.04 18.33 18.55

4.3.1. AlCrFeNiTi – the role of multiple “large” elements
System 1 in this study explores the effects of varying the Al content on the overall CCA
composition and crystal structure within the AlCrFeNiTi family. Figure 33 highlights top surface
SEM micrographs and corresponding XRD patterns for all samples within system 1, where each
row depicts a distinct Al composition (7 at.%, 15 at.%, and 33 at.%). As seen in the SEM
micrographs, all samples in system 1 feature nanocrystallites with roughly the same size (~1.6 nm,
see Table 2), shape, and orientation, where limited microstructural variations are observed with
changes in Al composition. This is also reflected in the XRD scans provided in Figures 33c, 33f,
and 33i, which show a single amorphous peak for each of the samples. Since all samples within
61

system 1 are amorphous regardless of Al content, it is possible that the other alloying elements are
driving the phase formation. For example, previous literature has stated that there is a critical Ti
content which could lead to the formation of an amorphous phase in MPEA films [101]. Therefore,
since each sample in system 1 has a Ti composition >10 at.% (Table 3), perhaps the critical Ti
content for the AlCrFeNiTi CCA family has already been reached.
Figure 33: Varied Al in AlCrFeNiTi family (System 1) - top surface SEM micrographs (a, b, d, e, g, and h) and
diffractograms (c, f, and i). Each row represents samples with the same Al content (7, 15, and 33 at% respectively).
Columns are split amongst samples that were in either the “top” or “bottom” substrate quadrant position during the
sputtering process, while diffractograms are color-coded based on that position.
In system 2, the Ti contribution to morphological changes is explored by varying the Ti
content between 5 and 35 at.%. Figure 34 includes the SEM micrographs and diffractograms for
62

samples within system 2, where each row represents a specific Ti composition (5 at.%, 13 at.%,
32 at.%). The SEM figures detail some morphological distinctions between the samples due to
compositional differences (see Table 3). The XRD patterns in Figures 34c, 34f, and 34i reveal a
phase change due to the varied Ti content, as an increase from 5 at.% to 13 at.% Ti leads to a
transition from a body-centered cubic (BCC) structure to an amorphous one. The average
crystallite size of the samples varied according to their crystallinity as shown in Table 2. Samples
with a Ti content greater than 10 at.% feature an amorphous phase in agreement with the
observations from system 1. Samples with less than 10 at.% Ti (S2-5Ti-T and S2-5Ti-B) exhibit a
crystalline phase, as noted by the XRD patterns in Figure 34c, where sample S2-5Ti-T display a
disordered BCC phase while sample S2-5Ti-B shows an ordered BCC phase with stronger peak
intensities. The difference between these two samples seems to depend on their respective Al
content. In Table 3, it can be seen that sample S2-5Ti-B has a higher Al content than any of the
other alloying elements (26.58 at.%), in contrast to S2-5Ti-T, which has 16.60 at.% Al. These
results imply that Al does play a role in phase formation, as increased Al content seems to
contribute to the degree of crystallinity within these samples.

63

Figure 34: Varied Ti in AlCrFeNiTi family (system 2) - top surface SEM micrographs (a, b, d, e, g, and h) and
diffractograms (c, f, and i). Each row represents samples with the same Ti content (5, 13, and 32 at% respectively).
Columns are split amongst samples that were in either the “top” or “bottom” substrate quadrant position during the
sputtering process, while diffractograms are color-coded based on that position.

The findings from systems 1 and 2 suggest the presence of a synergistic relationship
between Al and Ti in phase formation that should be further investigated. Therefore, additional
samples were synthesized to study the roles of Al and Ti in the composition space below 10 at.%
Ti. Figure 35 includes the top-surface SEM images and XRD patterns for samples within system
2 that are between 5 and 8 at.% Ti. Each column represents samples with the same Ti content (5
at.%, 7at.%, 8at.%). The rows are split amongst samples with “more” Al content, which have an
64

Al composition > 23 at.% (Fig. 35a – c), and samples with “less” Al, referring to those with a
higher Cr, Fe, and Ni content (Fig. 35d – f). The diffractograms for each sample, included in Figure
35g, are categorized by Al content as well. As the Ti content is increased from 5 at.% to 7 at.%,
the samples with “more” Al content transition from an ordered to a disordered BCC structure. Both
peak broadening and a decrease in peak intensity occurred (Fig. 35g), which are indicative of a
decrease in nanocrystallite size [270]. Upon comparison of the SEM micrographs in Figures 35a
and 35b, a decrease in nanocrystallite size from ~10 nm to ~7 nm (Table 2) can be observed with
an increase in Ti content. As highlighted in Figure 35c, a further increase in Ti content to 8 at.%
(sample S2-8Ti-B) results in a continued transition to an amorphous structure as further peak
broadening and a decrease in nanocrystallite size from ~7 nm to ~2 nm (Table 2) are noted in the
XRD pattern and SEM micrograph, respectively. In contrast, as Ti is increased from 5 at.% to 7
at.% in samples with “less” Al content, a transition from a disordered BCC structure to an
amorphous one occurs (Figure 35g). It appears that Al plays a role in the degree of crystallinity
below a specific Ti content threshold, while amorphous phases begin to form when the amount of
Ti exceeds 7 at.%. This finding can explain why the samples within system 1 feature an amorphous
phase and no structural alterations regardless of Al content, as each sample within system 1 has a
Ti content greater than 7 at.% (Table 3). Thus, the results from systems 1 and 2 further emphasize
the synergistic relationship between the two elements.
65

Figure 35: Top surface SEM micrographs (a – f) and diffractograms (g) for refined samples within system 2.
Diffractogram patterns and SEM micrograph borders are color coded by sample. Rows and diffractograms are split
amongst samples with either “more” or “less” Al content. Samples with “more” Al content have an Al composition
greater than 23 at%, whereas those with “less” Al content refer to samples with a higher proportion of Cr, Fe, and Ni
content in comparison to the Al content. Columns represent a specific Ti content (either 5, 7, or 8 at%, respectively).
66

Prior research on the individual effects of varied Al or Ti content within a given MPEA
system provides some key insights on their particular morphological contributions [65, 113, 243,
271-275], although the complex interplay of these two “large” elements found in this work has not
been previously addressed. Theoretical [276] and experimental studies have documented that Al
additions can lead to a face-centered cubic (FCC) to BCC phase transition in both bulk [67, 68,
76, 252, 253, 277, 278] and film samples [96, 98, 114, 267, 279]. This phenomenon has been
attributed to a lattice distortion effect, as the close packed FCC lattice must expand to
accommodate the larger Al atoms, thus transitioning to the less closely packed BCC structure [96,
98]. However, earlier work on CCA films and coatings suggests that an amorphous phase can be
favorable when lattice distortion is high, driven by a large atomic size difference [99, 100]. The
unique influence of Al is explained by Tang, et al., who state that the electronic structure of Al
favors covalent bonding with transition metals that have an incompletely filled d-shell,
contributing to the formation of crystal structures [280]. The role of Ti on phase formation has also
been attributed to lattice distortion effects, as it has caused the formation of heterogeneous and
dendritic structures in bulk systems [65, 97] and amorphous structures in film systems [101]. In
the current work, Al appears to be responsible for the formation of crystal structures and the degree
of crystallinity below a critical Ti content of 7 at.% due to its unique valence electron structure.
Conversely, increasing the amount of Ti promotes the formation of amorphous phases. In this
work, both Al and Ti are considered to be “large” elements as they possess atomic radii greater
than 140 pm (146.15 pm for Ti v.s. 143.17 pm for Al [81]). The similarity in their size leads to a
complex interplay between the two elements on morphological transformations. The findings here
seem to indicate that the elements with the largest atomic radii in a CCA arrangement will compete
to drive phase evolution, with their valence electron structures contributing to the types of phases
formed.

4.3.2. AlCoFeNiTi – the role of multiple “large” elements influenced by “small” element
substitution
To further explore the synergistic interplay of Al and Ti and whether comparable effects
translate to other systems, a similar experimental methodology is applied to a different CCA family
(AlCoFeNiTi). The overall compositions for system 3 (varied Al) and system 4 (varied Ti) are
67

included in Table 4. The influence of the “small” elements (i.e., transition metals with an atomic
radius of <130 pm) on phase formation is also investigated. Specifically, Cr is substituted by
similarly sized but structurally dissimilar Co. Both Cr and Co have an atomic radius of
approximately 125 pm, but Cr has a BCC structure and a valence electron concentration (VEC) of
6, whereas Co has a VEC of 9, a hexagonal close packed (HCP) structure at room temperature,
and an FCC structure at its melting temperature [81].

Table 4: Elemental composition derived from EDS data for systems 3 and 4 in the AlCoFeNiTi family.
AlCoFeNiTi
System Sample Al (at.%) Ti (at.%) Co (at.%) Fe (at.%) Ni (at.%)
3
S3-5Al-T 5.75 13.08 25.76 27.61 27.81
S3-5Al-B 6.47 19.63 23.51 24.82 25.57
S3-10Al-T 9.43 12.12 24.91 26.56 26.98
S3-10Al-B 10.42 19.39 22.52 23.91 23.75
S3-30Al-T 29.61 10.44 19.09 20.26 20.61
S3-30Al-B 30.54 15.29 18.36 17.19 18.63
4
S4-5Ti-T 11.39 3.93 28.55 27.01 29.21
S4-5Ti-B 17.32 4.25 24.83 26.63 26.97
S4-9Ti-T 9.65 8.84 25.99 27.72 27.89
S4-9Ti-B 15.43 9.34 23.86 25.66 25.72
S4-35Ti-T 7.91 32.10 19.31 20.40 20.28
S4-35Ti-B 12.06 34.34 17.95 17.42 18.24

Top surface SEM micrographs and XRD patterns for the samples within system 3 are
presented in Figure 36, where the rows are separated by specific Al content (5 at.%, 10 at.%, 30
at.%). Figures 36a – b, in the top row, highlight the samples with 5 at.% Al which feature
microstructural distinctions, including a twofold difference in naocrystallite size (Table 2), in
agreement with the diffractograms in Figure 36c, which detail a transition from a disordered BCC
structure to amorphous. A similar effect is found in the samples with 10 at.% Al (Figs. 36d – e),
which transition from an ordered “mixed” structure to amorphous, as seen by their XRD patterns
in Figure 36f. By contrast, both samples with 30 at.% Al (Fig. 36g – h) display similar
microstructural characteristics and an ordered cubic structure as illustrated in Figure 36i. It is
important to note that results from Table 4 indicate that samples with an amorphous phase (S3-
5Al-B and S3-10Al-B) have a Ti content greater than 19 at.% while samples below 19 at.% Ti
display crystalline structures. Their degree of crystallinity or ordering seems to depend on the Al
68

content (i.e., more Al yields a more ordered crystal structure). The overall results of system 3 have
the semblance of the synergistic relationship between Al and Ti found in the AlCrFeNiTi family
of CCAs, as each of the samples depict morphological differences due to both Al and Ti content.
However, there are two noticeable caveats in the results from system 3: first, there appears to be a
higher critical Ti content at which the amorphous phase begins to form, and second, Al does not
need to be the dominant element in the alloying arrangement to form ordered phases. For example,
as seen in Table 4, sample S3-10Al-T, which only has ~10 at.% Al, still shows an ordered phase
in its XRD pattern (Figure 36i). Thus, it seems that the distinctions in the synergistic relationship
between Al and Ti are influenced by the replacement of Cr by Co. These findings are further
supported by the results from system 4, which varied Ti content between 5 and 35 at.%. Figure 37
includes the top surface SEM images and diffractograms for all samples within system 4. Similar
to the findings from system 3, the samples with Ti content values below 19 at.% in system 4 exhibit
crystal structures, and the amount of Al content (see Table 4) affects the degree of crystallinity and
ordering. This observation is evidenced by the results in the first two rows of Figure 37 (5 and 9
at.% Ti). Samples in the left column (Fig. 37a and 32d), which consist of a lower Al content, have
a disordered “mixed” phase (Fig. 37c), while samples in the right column (Fig. 37b and 37e), which
contain a higher Al content, exhibit an ordered BCC structure (Fig. 37f). Samples with a Ti content
beyond 19 at.% (Fig. 37g – h) depict similar morphologies in their SEM micrographs and show
amorphous patterns (Fig. 37i); although, it should be noted that sample S4-35Ti-T does have
stronger peak intensities. In systems 3 and 4, ordered crystalline samples feature nanocrystallites
that are approximately ten times as large as their amorphous counterparts (Table 2). The trends in
systems 3 and 4 are consistent with each other, thus emphasizing the influence of the “small”
elements on phase formation.
69

Figure 36: Varied Al in AlCoFeNiTi family (system 3) - top surface SEM micrographs (a, b, d, e, g, and h) and
diffractograms (c, f, and i). Each row represents samples with the same Al content (5 10, and 30 at% respectively).
Columns are split amongst samples that were in either the “top” or “bottom” substrate quadrant position during the
sputtering process, while diffractograms are color-coded based on that position.

70

Figure 37: Varied Ti in AlCoFeNiTi family (system 4) - Top surface SEM micrographs (a, b, d, e, g, and h) and
diffractograms (c, f, and i). Each row represents samples with the same Ti content (5, 9, and 35 at% respectively.
Columns are split amongst samples that were in either the “top” or “bottom” substrate quadrant position during the
sputtering process, while diffractograms are color-coded based on that position.

The substitution of Co by Cr has been explored in previous works on bulk MPEAs with
relatively consistent results, but there is limited understanding on how this substitution would
affect phase formation and synergy in films containing multiple “large” elements. Researchers
have found that the addition of Cr and reduction of Co contributes to phase instability and the
formation of heterogeneous structures in the AlCoxCr1-xFeNi quinary family of CCAs [281] and
its quarternary derivative alloys AlCoFeNi and AlCrFeNi [282, 283]. This effect has been
71

attributed to the assessment that Co minimizes crystallographic mismatch while Cr induces
disorder in these types of systems [283]. However, such studies only explored alloying effects in
bulk materials, and none included Ti in their compositions. In order to visualize the role of Cr and
Co on phase formation, Figure 38 compares the Al and Ti content within the AlCrFeNiTi (Fig.
38a) and AlCoFeNiTi (Fig. 38b) families of CCAs, categorized by crystallographic phase. The
data points in dark blue are samples with an amorphous structure, light blue are “mixed” phase
samples, and yellow are crystalline samples. The dashed lines on the y-axes indicate the Ti
threshold at which amorphous phases form for each CCA family. For the AlCrFeNiTi family the
Ti threshold was determined to be approximately 7 at.%, while the AlCoFeNiTi family possessed
a threshold of about 19 at.%. It can be observed that the Ti threshold is much lower in samples
that contained Cr (Fig. 38a) than those that contained Co (Fig. 38b), and that crystalline phases are
more likely to form in the AlCoFeNiTi family than in the AlCrFeNiTi family. Thus, the trends
suggest that both the “large” elements and the “small” elements can impact phase formation in
these types of systems. These trends and their overall effect on the microstructure can be further
verified by measuring the influence of the phase transitions on the mechanical properties, which
is discussed in the next section.
Figure 38: Crystallography maps of samples in the AlCrFeNiTi (a) and AlCoFeNiTi (b) families of CCAs. Samples
are compared by their Al and Ti content and categorized by their respective crystallography: dark blue data points
indicate amorphous structures, light blue indicates “mixed” structures, and yellow indicates crystalline structures. The
red dotted lines on the y-axes represent the Ti threshold at which amorphous phases begin to form.

72

4.3.3. Nanoindentation
Nanoindentation is employed to further understand the complex relationship found
between the alloying elements within this work across phase transition zones. Reduced modulus
and hardness values for all samples are provided in Table 5. Samples are notated by the following
symbols: “●” are amorphous, “◊” are “mixed”, and “□” are crystalline. Samples in system 1 with
a higher Ti content (see Table 3) yielded lower values of modulus and hardness. In system 2,
samples with crystalline or “mixed” phases typically had higher modulus and hardness values than
those with amorphous phases, indicating a change in mechanical properties due to phase transitions
caused by increased Ti content. Note that sample S2-5Ti-T, which consists of a “mixed” structure,
had a slightly higher hardness (7.81 GPa) than sample S2-5Ti-B (7.69 GPa), which was crystalline.
These findings are in agreement with a previous review that suggested MPEA films and coatings
with amorphous phases will have lower hardness and modulus values than “mixed” or crystalline
samples [23]. While in some cases amorphous structures would feature higher hardness values
than coarse-grained crystalline structures, nanocrystalline materials have been shown to exhibit
superior strength in comparison to their coarse-grained counterparts [284] and amorphous
structures alike [285]. In system 3, samples with less Ti content (see Table 4) had hardness values
increase by 40% with increasing Al content, which coincides with samples becoming more
ordered, but modulus values decreased by 13% in the 5 at.% to 10 at.% Al range and increased by
27% in the 10 at.% to 30 at.% Al range. A similar result had been previously reported by Sun, et
al. in AlxCoCrCuFeNi, where there was an initial decrease in modulus with the addition of Al,
followed by an increase in modulus attributed to phase transitions [278]. Amorphous samples in
system 3 showed an increase in both modulus and hardness with increasing Al content, however,
these samples had lower hardness values than the crystalline or “mixed” samples of this set. In
system 4, crystalline samples also exhibited higher hardness and moduli values than “mixed”
samples; however, the “mixed” samples had a slightly lower hardness than the amorphous samples.

73

Table 5: Reduced modulus and hardness values determined via nanoindentation. Samples are notated based on their
respective crystallography, where “●” indicates an amorphous structure, “◊” indicates a mixed structure, and “□”
indicates a crystalline structure.
AlCrFeNiTi
System 1 – Varied Al System 2 – Varied Ti
Sample
Reduced
Modulus
(GPa)
Hardness
(GPa)
Sample
Reduced
Modulus
(GPa)
Hardness
(GPa)
S1-7Al-T
●
153.49 ± 3.02 7.08 ± 0.19 S2-5Ti-T
◊
157.27 ± 4.27 7.81 ± 0.27
S1-7Al-B
●
138.72 ± 3.20 6.87 ± 0.18 S2-5Ti-B
□
161.60 ± 7.19 7.69 ± 0.50
S1-15Al-T
●
148.06 ± 3.45 7.13 ± 0.18 S2-7Ti-T
●
144.12 ± 4.07 7.34 ± 0.19
S1-15Al-B
●
142.71 ± 4.19 6.99 ± 0.19 S2-7Ti-B
◊
155.64 ± 5.57 7.41 ± 0.31
S1-33Al-T
●
127.62 ± 4.74 7.02 ± 0.23 S2-8Ti-T
●
155.00 ± 4.27 7.18± 0.18
S1-33Al-B
●
139.74 ± 3.80 7.24 ± 0.22 S2-8Ti-B
◊
164.34 ± 4.33 7.27 ± 0.20
S2-13Ti-T
●
150.23 ± 4.44 7.24 ± 0.20
S2-13Ti-B
●
148.00 ± 5.79 7.28 ± 0.23
S2-32Ti-T
●
131.96 ± 3.31 6.80 ± 0.15
S2-32Ti-B
●
140.83 ± 3.01 7.14 ± 0.15
AlCoFeNiTi
System 3 – Varied Al System 4 – Varied Ti
Sample
Reduced
Modulus
(GPa)
Hardness
(GPa)
Sample
Reduced
Modulus
(GPa)
Hardness
(GPa)
S3-5Al-T
◊
152.89 ± 3.55 7.02 ± 0.21 S4-5Ti-T
◊
154.86 ± 4.56 6.68 ± 0.22
S3-5Al-B
●
140.79 ± 2.30 6.71 ± 0.11 S4-5Ti-B
□
158.22 ± 6.14 7.18 ± 0.41
S3-10Al-T
◊
133.65 ± 4.70 7.47 ± 0.27 S4-9Ti-T
◊
152.63 ± 3.99 6.99 ± 0.23
S3-10Al-B
●
145.66 ± 3.04 7.00 ± 0.16 S4-9Ti-B
□
165.44 ± 5.85 7.57 ± 0.31
S3-30Al-T
□
169.78 ± 4.96 9.83 ± 0.33 S4-35Ti-T
●
139.55 ± 2.62 7.25 ± 0.17
S3-30Al-B
□
164.43 ± 5.90 8.63 ± 0.47 S4-35Ti-B
●
144.23 ± 2.76 7.21 ± 0.15

Overall, the synergistic relationship between Al and Ti contributes to the mechanical
properties within the systems studied in this work. Below the critical amount of Ti in both families
of alloys, the amount of Al will influence the degree of crystallinity in the samples, thereby
affecting the mechanical properties. Non-amorphous samples with “more” Al compared to their
counterparts typically had higher modulus (155 – 170 GPa) and hardness values (7.2 – 10 GPa)
due to ordering. It was also found that additional Ti resulted in a decrease in the mechanical
property values (modulus range of 125-155 GPa, hardness range of 6.5 – 7.3 GPa), as more Ti led
to the formation of amorphous phases. Samples in the current study exhibit hardness and moduli
74

comparable to those of other MPEA systems [245, 263, 278, 286-288], both bulk and film alike,
aligning with the expected notable mechanical properties of these types of materials.

4.4. Conclusions
The results from this study highlight sputtering as a tool to control individual elements within
CCA families in order to examine how their atomic characteristics contribute to phase formation
and crystallinity. It was found that the “large” elements have a synergistic relationship in which
they compete for phase formation, such that a critical threshold exists at which amorphous
structures begin to form. The “small” elements can impact this complex interplay, altering the
critical threshold and causing different phases to form, as the replacement of Cr by Co changed
the crytstalline to amorphous threshold from 7 at.% Ti to 19 at.% Ti. Crystallites were typically an
order of magnitude larger in ordered samples than in amorphous samples throughout all systems.
Mechanical properties, as derived by nanoindentation, were influenced by these phase changes as
well, where amorphous samples generally had lower hardness and moduli than than their
crystalline or “mixed” phase counterparts. While the results presented in the current work can
guide the synthesis of CCA films, it should be noted that these trends may not translate across
synthesis methods, particularly due to the high cooling rate of PVD techniques which can mitigate
phase separation; therefore, further studies are needed to compare how trends translate across
synthesis techniques. However, the crystallography maps illustrated in this work may provide a
guideline for phase transitions and serve as a model for future alloy design across synthesis
methods.

75

5. Chapter 5: Influence of microstructural distribution in heterogeneous
nanomaterials
A version of the following work is published as a journal article titled Distribution of
nanodomains in heterogeneous Ni-superalloys: Effect on microstructure and mechanical
deformation in Acta Materialia, 252, 118940, (2023) DOI: 10.1016/j.actamat.2023.118940.

5.1. Introduction
Heterogeneous nanostructured materials (HNMs) have garnered significant attention due to
their improved strength-ductility synergy compared to nanocrystalline or ultrafine-grained
structures. The enhanced mechanical behavior is attributed to nanoscale features and a variety of
domain sizes with differing strengths, which lead to a plastic gradient during deformation and
increased work hardenability [149, 150]. Several top-down fabrication techniques have been
employed to synthesize HNMs, including surface mechanical treatments [148] and rolling
techniques [149, 289]. These methods have been used to produce HNMs including bimodal [290],
harmonic [291-293], lamellar [294], and gradient structures [289] by severe or dynamic plastic
deformation and subsequent annealing [149]. However, these synthesis techniques are limited to
materials that can sustain large mechanical deformations, thus lacking the ability to precisely tailor
grain size, multiple phases, and complex compositions [289].
Therefore, an opportunity exists to leverage bottom-up approaches such as electrodeposition
and magnetron sputtering for synthesizing HNMs with increased compositional and
microstructural complexity, featuring domains of varying grain morphologies, phases, and
chemical composition. Electrodeposition has been utilized to produce hierarchical heterogeneous
materials by manipulating the deposition conditions [295]; however, this technique is mostly
restricted to single element or binary alloy systems [296]. Magnetron sputtering, a physical vapor
deposition (PVD) technique, can be used to synthesize a wide range of compositions [297], grain
sizes, and microstructures [26], including nanostructured materials [40-42] and heterogeneous
nanostructures in the as-prepared state, such as nanotwinned (NT) materials [143-146]. Tailorable
deposition conditions allow for enhanced control over material composition and the distribution
of nanodomains [289], which include microstructural features, phases, and precipitates that are
between 1 and 200 nm [298]. Additionally, intrinsic and extrinsic stresses that arise during the
76

sputtering process [176] can facilitate heterogeneous structural formations upon heat treatment,
such as bimodal grain distributions, abnormally large grains (ALGs), and unexpected precipitation
[39, 41, 143]. Altering the stress distribution and profile in sputtered films can thus be leveraged
to further expand HNM complexity. In magnetron sputtering, managing the deposition conditions,
such as substrate bias, temperature, and working pressure, can have an effect on the sign and
magnitude of stress in the film [176, 299]. Moreover, the substrate material can influence the stress
profile throughout the film thickness due to lattice or coefficient of thermal expansion mismatch
[174, 176, 191], thereby facilitating unique distributions of nanodomains post-heat treatment.
In bulk and coarse-grained age-hardenable Inconel 725, heat treatments have been used to
facilitate the formation of standard microstructural features such as γ”, γ’, and carbide
precipitation. More recently, research by Bahena et al. on sputtered NT Inconel 725 demonstrated
that stress gradients throughout the film thickness can facilitate the nucleation of microstructures
outside of these standard features upon heat treatment, including novel nanodomains such as rafted
structures, δ-phase precipitates, and ALGs [143]. In general, the effects of γ”, γ’, and carbide
precipitation in bulk Ni-superalloys are well understood, as they have been shown to improve the
yield and tensile strength [159], thermal stability [300] and strength at elevated temperatures [163,
164]. In regards to rafted structures, δ-phase precipitates, and ALGs in bulk Ni-superalloys, studies
have only focused on the individual contributions of these features, which have revealed rafted
structures improving creep resistance [168, 301], δ-phase enhancing ductility [302], and ALGs
leading to structural degradation [170, 171]. However, there is a knowledge gap about the
interaction and effects of these standard and novel features, especially within the context of
producing heterogeneous nanodomains. By utilizing a versatile synthesis technique that can
develop complex microstructures, previously unexplored HNM feature combinations can be
formed. Thus, the global effect of all these features, their distribution, and interactions on
mechanical behavior can for the first time be realized.
In this study, NT Inconel 725 films were sputtered onto two types of substrates, namely
Corning Eagle 2000 glass and Si (100), to produce two distinct stress profiles, which influenced
the distribution of nanodomains post-heat treatment and the resulting mechanical deformation. As-
sputtered and heat-treated films were tested using both Vickers micro-indentation and
nanoindentation techniques to study the mechanical deformation behavior and properties. The as-
77

sputtered, heat-treated, and post-deformation films were thoroughly examined via microscopy
techniques to evaluate the role of the substrate type on microstructural evolution and mechanical
response. Overall, this manuscript highlights how altering the distribution of the nanodomains by
changing the as-sputtered stress profiles, in combination with heat treatments, can be used to tailor
heterogeneous microstructures and the mechanical response, thereby providing valuable insight
on the design of future HNMs with increased complexity.

5.2. Experimental Methods
Films were deposited via direct current (DC) magnetron sputtering at 1500 W from a 7.6 cm
working distance, a working pressure of 0.3 Pa, and a sputtering rate of 5.9 nm/s, reaching a
substrate temperature of 500°C. Films were sputtered to a thickness of ~8 μm, measured using an
AMBiOS XP-2 Profilometer. An Inconel 725 planar target (Plasmaterials, inc.) was used to sputter
onto 25 mm diameter Corning Eagle 2000 glass or Si (100) substrates. The substrate materials
were selected based on their distinct physical and mechanical properties, which can affect the stress
profile of the films, as seen in Stoney’s equation (Equation 8) [202].
Where σstoney is the residual stress of the film, Es is the elastic modulus of the substrate, ts is the
thickness of the substrate, tf is the thickness of the film, υs is Poisson’s ratio of the substrate, and
R is the radius of curvature of the film. The Corning Eagle 2000 glass substrate has an elastic
modulus which is less than half of that of Si (100) (70.9 GPa v. 165 GPa) [303, 304] and is twice
as thick (500 μm v. 250 μm). Thus, each substrate will exhibit a different residual stress based on
Equation 8 as shown in Figure 39, which highlights that the samples deposited on Si and glass will
experience differences in their residual stress profiles for a wide range of curvature values. It
should be noted that high residual stresses in the films caused partial detachment from the
substrate, such that the actual radius of curvature and residual stress could not be measured via
profilometry.
Prior to performing heat treatments, samples were fully removed from their respective
substrates to obtain free-standing films. Pieces of the films were heat treated by a modified version
of the standard Inconel 725 aging treatment, as guided by the work by Bahena et al. [143] using a
GSL1100X tube furnace (MTI Corporation) at a constant temperature of 730°C for 5 h under a
78

vacuum pressure of 7 x 10
-5
Pa. Once the heat treatment had been completed, the samples were
furnace cooled at a rate of 5°C/min.
Top-surface morphology was observed via scanning electron microscopy (SEM) (FEI
Helios G4 P-FIB UXe) using a beam current of 0.2 nA and an accelerating voltage of 20 kV. Top
surface compositions were acquired via scanning electron microscopy/energy-dispersive x-ray
spectroscopy (SEM/EDS) (FEI G4 Helios P-FIB UXe) at 20 kV. The nominal compositions of the
films are included in Table 6 and are compared to standard industry ranges of Inconel 725 [205].
Cross-sectional micrographs in both the as-sputtered and heat-treated state were examined using
transmission electron microscopy (TEM), performed by a JEOL JEM-2100F with both STEM and
EDS capabilities. TEM lamellae were prepared by the focused ion beam (FIB) method using a FEI
G4 Helios P-FIB UXe. The region of interest was protected from the ion beam by a deposited ~4
μm layer of W. Transmission Kikuchi diffraction (TKD) was obtained using a FEI G4 Helios P-
FIB UXe with an Oxford Symmetry detector. This data was used to observe grain orientation,
grain size, and morphological information and was correlated to STEM images of the as-sputtered
and heat-treated samples.

Table 6: top surface compositional data for as-sputtered (AS) and heat-treated (HT) samples in wt %. Composition
ranges for standard Inconel is provided for reference.
Sample Ni Cr Mo Fe Nb Ti Al Si
AS glass 55.2 24.2 7.6 7.4 3.5 1.4 0.6 0.1
HT glass 54.0 24.5 8.3 7.3 3.5 1.4 0.8 0.2
AS Si 55.2 24.2 7.6 7.4 3.5 1.5 0.5 0.1
HT Si 53.7 24.5 8.3 7.5 3.4 1.4 1.0 0.2
Standard
55 –
59
19 –
22.5
7.0 –
9.5
balance
2.7 –
4.0
1.0 –
1.7
0.0 –
0.35
0.20
max

Mechanical data was acquired via both Vickers micro-indentation and nanoindentation
methods. Vickers micro-indentation (LECO LM-100) was performed using a force of 10 g to
maintain an indent depth smaller than 1/10 of the film thickness. Five Vickers indents were made
79

on each as-sputtered and heat-treated sample. Nanoindentation was performed via a Hysitron
Triboindenter with a 50 nm Berkovich tip using a force-controlled and constant loading rate
function. Indents were performed in a 5x5 array positioned 5 µm apart for each of the as-sputtered
and heat-treated samples.

5.3. Results and Discussion
5.3.1. As-sputtered Microstructure
Two distinct heterogeneous samples were fabricated by changing the substrate type,
allowing for two different stress profiles, which is reflected in the microstructure of the films. As
a non-equilibrium process, magnetron sputtering can introduce complex residual stress profiles in
the deposited films, due to components of intrinsic and extrinsic stress [305]. Intrinsic stresses
develop directly during the deposition process due to film nucleation and growth mechanisms
[306], such as ion peening, transport of adatoms into grain boundaries, and reduction of film
volume [307]. Extrinsic stresses are due to any external forces on the film-substrate system,
including changes in thermal expansion, exposure to electromagnetic fields, and mechanical
effects [305, 306]. Throughout the film growth process, the magnitude and signs of each
component will change, leading to a gradient in the total residual stress at different points in the
film thickness [307]. For example, the greatest magnitude of stress is typically found near the
substrate-film interface due to lattice mismatch, coefficient of thermal expansion mismatch, and
atomic peening [174, 176, 191, 308]. The stress is then expected to gradually decrease as the film
grows thicker [309], with local stress gradients caused by any grain misorientation from the
preferred material texture [310]. In this work, the only experimental variable that was changed for
each sample was the substrate type, which can influence both the intrinsic and extrinsic stresses in
the film growth process [174, 191]. Therefore, a difference in the stress gradient and total stress
should be expected between each sample.
To estimate the total stress present in each sample, Stoney’s equation (Equation 8) was
leveraged to calculate the residual stress as a function of radius of curvature for each type of
substrate. These calculations are plotted in Figure 39, which shows the differences in average
global stress for deposited ~8 µm thick Inconel 725 films. The residual stress values for samples
deposited on Corning Eagle 2000 glass are presented in orange while those deposited on Si (100)
80

are in blue. The stress profiles in Figure 39 show that a negative radius of curvature results in a
tensile residual stress (Fig. 39a) and a positive radius of curvature leads to compressive residual
stress (Fig. 39b). Physical observations of the films suggest tensile stress behavior, as the films
partially delaminated from the substrate upon removal from the vacuum chamber. Furthermore, at
the 500°C deposition temperature, the coefficient of thermal expansion (α) of the substrates ( α
Si
=
4.15x10
-6
⁰C
-1
, α
glass
= 3.61x10
-6
⁰C
-1
) are smaller than that of the film (α
Inc725
=14.1x10
-6
°C ) [303,
311, 312], resulting in films that will have residual stress in the tensile regime [191]. In Figure
39a, it can be observed that the difference in residual stress between the two substrates ranges from
~500 MPa at a curvature of -0.5 m
-1
to ~2300 MPa at a curvature of -0.1 m
-1
. The calculations
presented in Figure 39 provide a guide for the distinct stress conditions that are expected in each
type of film, which would then facilitate unique heterogeneous microstructures before and after
heat treatment.
Figure 39: Calculated changes in residual stress as a function of radius of curvature based on Stoney’s equation for an
~8µm thick Inconel 725 sample deposited on glass (orange) and Si (blue) substrates. (a) Shows how a tensile residual
stress is present for negative radii of curvature while (b) shows a compressive residual stress for positive radii of
curvature.

A thorough investigation of the as-sputtered microstructure using multiple characterization
techniques is provided in Figures 40 and 41. Top surface SEM micrographs (Figs. 40a and 40b),
cross-sectional TEM micrographs (Figs. 40c and 40e), calculated grain width distributions (Figs.
81

40d and 40f) and XRD diffractograms (Fig. 40g) are provided for films deposited on glass, notated
in red, and Si, notated in green, respectively. Average grain widths and twin thicknesses, derived
from over 100 grains and twins for each type of sample, are included. Grain widths were selected
as the unit of measurement for the grains as they are columnar and run the length of the entire
thickness of the film. Film growth direction is indicated by the yellow dotted arrows in Figs. 40c
and 40e. Identifiable differences due to substrate type in the as-prepared state can be seen from the
top surface micrographs (Figs. 40a, b), grain width distributions (Figs. 40d, f), and diffractograms
for each sample (Fig. 40g). The sample deposited on glass exhibited a smoother surface
morphology and a slightly smaller grain width of 20.2 nm when compared to 33.4 nm for the film
deposited on Si. Differences in the morphology and texture can be attributed to the crystallographic
orientation of the substrate, which can bias texture and cause a greater degree of surface roughness
[313], whereas amorphous substrates, like glass, allow for the development of stronger uniform
textures [127, 314]. Regardless of substrate type, a fully NT columnar structure, composed of very
fine nanotwins that are 0.6 nm thick, forming perpendicular to the growth direction of the film
(Figs. 40c, e) is observed. Both the low stacking fault energy typical of Inconel alloys (< 30 mJ/m
2
)
[315] and high deposition rate (~6 nm/s) used during synthesis can contribute to the formation of
very fine nanotwins [145, 147]. Overall, the substrate type is found to influence top surface
morphology, grain size, and texturing, while the deposition conditions affect the microstructure.
Figure 40: As-sputtered characterization of samples deposited on (red) corning eagle glass and (green) Si <100>
substrates, including (a, b) top surface SEM micrographs, (c, e) bright field TEM micrographs with yellow arrow
indicating growth direction, (d, f) grain width distributions, and corresponding (g) XRD patterns.
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The relationship between substrate effects and cross-sectional microstructure are further
examined in the dark field (DF) STEM micrographs and TKD patterns presented in Figure 41.
Figure 41a includes the DF STEM micrograph, TKD pattern, and inverse pole figure (IPF) for the
sample deposited on glass, while Figure 41b presents the sample deposited on Si. The red region
at the bottom of the TKD pattern in Figure 41b is due to the (100) orientation of the Si substrate.
Both figures highlight the region of the films near the substrate interface, where some grain
misorientation occurs. The TKD patterns suggest that the misoriented region is slightly larger in
the glass sample (~800 nm) than in the Si sample (~200 nm). Beyond the misoriented region, both
samples feature a strong columnar (111) texture consisting of a dense NT structure throughout
each grain, as indicated by the IPFs. The grain misorientation is likely due to a combination of
lattice misfit between the substrate and film, defects generated by atomic peening [176, 308], and
early-stage film growth kinetics [122, 123]. As the grains transition from misoriented to the
preferred texture in the growth direction, the film stress reaches a steady state dependent on the
mobility of the material, deposition temperature, and deposition rate [316], thus facilitating
gradients in stored energy and film stress throughout the film thickness [62, 310]. The effects of
stored energy and stress gradients due to grain misorientation were identified in the study by
Bahena et al., as the gradients were found to facilitate unique nanodomain formation throughout
the film upon heat treatment [143]. In this work, it is expected that the difference in the length of
the misoriented region in the two samples leads to different stress gradients, thereby contributing
to distinct nanodomain distributions post-heat treatment. These effects will be examined more
closely in the next section.
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Figure 41: Dark field STEM micrographs of as-sputtered (a) fine NT and (b) coarse NT sample. Misoriented growth
region between substrate and columnar regions is indicated by white dotted arrow. TKD patterns with pole figure
provided for each micrograph, highlighting misorientation in area close to substrate. Growth direction of both samples
indicated by orange arrow inset of (a).

5.3.2. Heterogeneous Nanodomain Formation
To evaluate the role of the different stress profiles on nanodomain distribution, heat
treatments were carried out on each sample at 730⁰C for 5 hours to facilitate the formation of
complex heterogeneous microstructures in each film, as guided by the work by Bahena et al [143].
The resultant microstructures for the films deposited on glass and Si are presented in the DF STEM
micrographs, TKD patterns, and EDS maps in Figures 42 and 43, respectively, where the growth
direction is indicated by the black arrow on the left of each figure. Column (a) of each figure
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features a micrograph of the total film including insets of feature size distributions per region.
Column (b) includes magnified micrographs of three Regions: Region I is the area closest to the
substrate, Region II shows the middle area of the film, and Region III is the area close to the free
surface of the film. Annotations for the nanodomains highlighted in column (b) are as follows:
black dotted lines for ALGs, yellow dashed lines for annealing twins, blue solid lines for δ-phase
precipitates, green solid lines for carbide precipitates, and purple solid lines for rafted structures.
Column (c) displays TKD patterns and EDS maps for a small section of each Region, with
corresponding IPFs for identified phases including those for Ni-superalloys, M23C6 carbides, and
Ni3(Nb, Ti) δ-phase. Since each film is the same thickness, important distinctions in the
distribution of nanodomains in each Region across both samples due to different stress states will
be compared in the following subsections.

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Figure 42: (a) DF STEM micrograph of gradient heterogeneous sample post-heat treatment. Micrograph is divided
into three Regions: I, II, and III, where feature size distributions are provided in the insets. (b) Magnified micrographs
of each region with annotations provided for notable nanodomains (see legend). (c) TKD patterns and EDS maps of
selected area of each Region, highlighted in orange. Average feature sizes for each section included. IPFs provided
for orientations of identified phases in each TKD pattern. White bars on TKD patterns indicate 500nm scale.

86

Figure 43: (a) DF STEM micrograph of uniform heterogeneous sample post-heat treatment. Micrograph is divided
into three Regions: I, II, and III, where feature size distributions are provided in the insets. (b) Magnified micrographs
of each region with annotations provided for notable nanodomains (see legend). (c) TKD patterns and EDS maps of
selected area of each Region, highlighted in orange. Average feature sizes for each section included. IPFs provided
for orientations of identified phases in each TKD pattern. White bars on TKD patterns indicate 500nm scale.

5.3.2.1. Region I – Substrate Interface
In Region I for both Figures 42 and 43, the nanocrystalline equiaxed grain area (notated by
“NC”) and the columnar nanotwinned grains (notated by “NT”) are indicated by the black arrows.
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For the sample sputtered on glass (Fig. 42), a base structure of nanocrystalline equiaxed grains
(~470 nm) is identified close to the substrate interface, followed by a columnar NT grain structure
with globular precipitation occurring at the grain boundaries. In the area close to the substrate, a
high degree of grain misorientation is attributed to high residual stress and stored energy [166,
167], which induces complete recrystallization in this area upon heat treatment, leading to the
formation of stable nanocrystalline equiaxed grains [143]. TKD patterns and EDS maps for this
region confirm that the precipitates are Cr-rich M23C6 carbides, which tend to form at high angle
grain boundaries at low ageing conditions [317], and that the columnar grain structure with strong
(111) texturing is preserved due to improved thermal stability via the carbides at the grain
boundaries and high density of nanotwins [318].
By contrast, for the sample deposited on Si (Fig. 43), a smaller nanocrystalline equiaxed
region (~85 nm) is identified near the substrate interface, while ALGs, Nb-rich δ-phase
precipitates, carbide precipitates, and rafted structures are all seen as well. The smaller
nanocrystalline equiaxed region can likely be attributed to a shorter misoriented grain region in
the as-sputtered sample deposited on Si compared to glass (see Fig. 41), highlighting the effects
of misorientation on nanodomain formation post-heat treatment. The NT columnar grains also
appear to have wavier, distorted boundaries compared to those in the sample deposited on glass,
indicative of a transition to equiaxed grains. Overall, the sample deposited on Si exhibits higher
microstructural complexity than the sample deposited on glass in the region closest to the substrate,
highlighting differences in the stored energy profile throughout each sample.

5.3.2.2. Region II – Middle Section
The evolution of the stored energy profile due to residual stresses throughout the film
thickness can be emphasized further in the middle region, which spans ~4 – 6 μm above the
substrate. In Figures 42 and 43, the NT columnar grain structure is lost, as the microstructure
transitions to one composed of ALGs, which feature bands of annealing twins (~10 nm thick) and
δ-phase precipitates running the length of the grains, along with continued M23C6 carbide
precipitation. In the TKD patterns, red lines that border different features identify annealing twin
boundaries that form along the ALGs. Previous research has found that ALGs promote the
formation of annealing twins [319-321], which then serve as nucleation sites for δ-phase
88

precipitates [169, 322, 323]. For the sample deposited on glass, most of the ALGs retain the
preferred (111) texture of the as-sputtered film while some are misoriented, as indicated by the
IPFs. In contrast, for the sample deposited on Si (Fig. 43), the majority of ALGs are misoriented,
as seen in the TKD pattern for this Region, while rafted structures form as well. The orientation of
the ALGs is dictated by two possible thermal activation mechanisms: (1) a strain-induced
boundary migration (SIBM) process, in which changes in stored energy throughout the film due
to residual stresses causes the boundaries of low energy grains to migrate towards high energy
regions, yielding low energy grains with the same crystallographic orientation as the parent grain
[324], or (2) a nucleation-based recrystallization mechanism, in which low energy grains grow at
the expense of high energy neighbors, leading to an abnormal recrystallization process and
misoriented grains [167, 325]. The high degree of ALG misorientation indicates that the
nucleation-based abnormal recrystallization mechanism is dominant in the sample deposited on
Si, further validating that the stored energy profile due to residual stresses is different in each
sample, as abnormal recrystallization typically occurs at higher stored energy conditions than
SIBM [326].

5.3.2.3. Region III – Free Surface
Differences in the stored energy profile in each film are emphasized further when
examining the Region close to the free surface, which spans ~6 – 8 μm above the substrate. In
Figure 42, all unique nanodomains are identifiable, including rafted structures confined in an area
between ~6 and 7 μm of the film thickness; thus, making this the most complex Region in the
sample deposited on glass. Since the stored energy in deposited films usually tends to decrease in
the growth direction [308], it is anticipated that the SIBM process will be dominate towards the
free surface of the film, as it typically occurs at low-moderate stored energy conditions [326],
thereby facilitating the formation of rafted structures and enlarged ALGs with the preferred
orientation. Previous research has found that the rafting of grains can be caused by SIBM via local
reductions in chemical free energy, decreases in stored energy, or grain boundary migration [327,
328]. The TKD pattern and EDS maps highlight bands of Nb-rich δ-phase precipitates running
across the length of one of the ALGs, generating at the annealing twin boundaries, emphasizing
the evaluation from Section 5.3.2.2. M23C6 carbides are also observed at the free surface of the
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film. By contrast, the high degree of misoriented ALGs is sustained in the sample deposited on Si
(Fig. 43), suggesting that the stored energy profile is similar from Region II to Region III. Each of
the unique nanodomains are also identified in this region, with the TKD pattern and EDS maps
highlighting a high density of Ni3Nb δ-phase precipitation. The size of the ALGs were also found
to gradually decrease, eventually transitioning back to a columnar NT structure in the growth
direction towards the free surface, as highlighted by the STEM micrograph and TKD pattern.

5.3.3. Graphical Nanodomain Distribution
Feature size distributions were affected by the different stress profiles in each sample, as
shown in Figures 42 and 43. In the sample deposited on glass, a gradient size distribution of the
nanodomains was found to gradually increase from 58 nm to 233 nm in the growth direction, while
the sample deposited on Si saw an increase in feature size from 99 nm in Region I to 198 nm in
Region II, but a slight decrease in feature size to 157 nm in Region III. Thus, including the as-
sputtered and heat-treated samples, this work presents four distinct heterogeneous microstructures
at different length scales: two NT structures with coarser or finer grain width distributions, a HNM
with a uniform distribution of precipitated nanodomains and feature sizes, and a HNM with a
gradient distribution of feature sizes. From this point, the samples will be referred by the following
notations: coarse-grained NT, fine grained NT, uniform HNM, and gradient HNM. “Uniform” in
this case refers to the distribution of nanodomains throughout the entire film thickness. To better
visualize the types and distribution of the nanodomains in each microstructure, a graphical
representation of each sample is provided in Figure 44. Figure 44a represents both the coarse- and
fine-grained fully NT structure as seen in the as-deposited samples, Figure 44b is the HNM with a
uniform distribution of nanodomains, and Figure 44c is the HNM with a gradient feature size
distribution. The growth direction of the films is indicated by the black arrow on the left of Figure
44a. Here, the relatively consistent feature size and uniform dispersion of all the nanodomains
throughout the entirety of the sample in Figure 44b can be seen compared to the gradual increase
in feature size in Figure 44c. Notably, fewer ALGs are found near the free surface in the uniform
HNM, while the ALGs increase in size towards the free surface in the gradient HNM. The
difference in feature size distribution in the heat-treated films can be explained by the ALG
activation processes. While both samples have reduced stored energy towards the free surface of
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the film, the low stored energy allows for preferential growth of ALGs via SIBM in the gradient
HNM, as low energy grains subsume their high energy neighbors [167, 319]. In comparison, for
the uniform HNM, the feature size remains relatively consistent throughout, as most of the ALGs
are formed by nucleation based abnormal recrystallization, which yields smaller grains due to
limited nucleation sites [324, 329]. Clearly, two unique nanodomain distributions are developed
due to the distinct stress profiles in each film and subsequent heat treatment, which is expected to
have important ramifications on the respective mechanical behavior of each sample.
Figure 44: Schematic illustration of (a) NT heterogeneous nanostructured material (HNM), (b) uniform HNM, and (c)
gradient HNM. Abnormally large grains are indicated by the grey shapes, delta phase by blue streaks, Cr-C by green
spheres, rafted structured by striped, purple pattern, annealing twins by gold lines, and nanocrystalline structures by
grey octagonal shapes. Growth direction is indicated by the black arrow to the left of (a).

5.3.4. Deformation Behavior due to Nanodomain Distribution
As mentioned in the introduction, the combined effect of the nanodomains on mechanical
deformation has yet to be explored. In order to address this, nanoindentation and Vickers micro-
indentation tests were carried out on the top surface of both the as-sputtered and heat-treated films,
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using Region III as a representative area due to its microstructural complexity and high density of
nanodomains, as highlighted by Figure 44. Although tensile tests would have been a preferred
method of examining the mechanical behavior of the entire film, the high residual stresses made it
difficult to machine tensile specimens. Table 7 presents the summary of mechanical data for the
as deposited and heat-treated samples, with values for solution annealed and age-hardened bulk
Inconel 725 included for reference [311]. The modulus for Inconel 725 is 204 GPa [311] while the
reduced modulus for all samples, determined via nanoindentation, is approximately 200 GPa.
Variance in the modulus values for each sample are consistent with the orientation effects on
modulus seen in single crystal Ni, which ranges from 120 GPa in the (100) direction to 206 GPa
in the (111) direction [330]. All samples in this study exhibit improved strengthening compared to
their bulk counterparts, which can be partially attributed to the nanoscale feature sizes, including
the dense NT structures [331-333]. While the trends in the Vickers data suggests that the heat
treatments lowered the hardness, the nanoindentation data showed a higher hardness for the
uniform HNM compared to the gradient HNM and coarse-grained NT sample. The discrepancy
between the data of the two indentation tests can be attributed to the shallower contact depth and
localization effects of nanoindentation [334]. In particular, the uniform HNM has a greater degree
of heterogeneity in the x-y plane near the surface of the film compared to the gradient HNM, which
features more heterogeneity in the growth direction. Therefore, the higher observed
nanoindentation hardness in the uniform HNM is likely a product of a 26% volume fraction of
M23C6 carbide precipitates and NT columnar grains near the surface. These results are supported
by the nanoindentation load-displacement plots for each representative microstructure, which have
been provided in an expanded version of Figure 44 in the Appendix (Section C., Figure 56). These
plots highlight much more variance in the uniform HNM compared to the NT microstructures and
the gradient HNM, thus emphasizing the localization effects occurring in the uniform HNM during
nanoindentation. In the case of the Vickers data, which provides a more global response, the graded
feature size distribution of the gradient HNM, combined with a 35% volume fraction of M23C6
carbides, contributed to higher hardness compared to the uniform HNM [289], despite a lower
density of NT structures and larger average feature size in Region III. While the mechanical data
from the indentation tests provides partial information on the overall deformation, further
characterization can highlight the contributions of the individual nanodomains. Microstructural
92

characterization was performed on the Vickers indents, which provide information on a larger
volume of nanodomains, allowing for a more comprehensive view of the deformation.

Table 7: Mechanical properties via indentation for all samples from this study compared to literature values* [311].
**Indentation hardness for solution annealed and age-hardened determined from Rockwell hardness in literature.
Type
Indentation
Hardness (GPa)
Nanoindentation
Hardness (GPa)
Fine-grained NT 8.29 9.59
Coarse-grained NT 7.47 7.57
Uniform HNM 7.04 9.58
Gradient HNM 7.47 8.15
Solution annealed* 1.72** -
Age-hardened* 3.40** -

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Figure 45: SEM micrographs (a-d) and BF STEM micrographs (e-h) of Vickers indents for fine-grained NT structure,
coarse-grained NT structure, uniform HNM, and gradient HNM. All Indents were performed using a 10 g load.

Figure 45 includes top surface SEM micrographs (Fig. 45a – d) and cross-sectional BF
STEM micrographs (Fig. 45e – f) of each sample after Vickers micro-indentation testing. The
samples from left to right are as follows: fine-grained NT structure, coarse-grained NT structure,
uniform HNM, and gradient HNM. For the NT samples (Fig. 45a, b), some material pile-up on the
indent edges can be seen, which has been observed in other studies of highly NT films [230, 335-
337]. Interestingly, the indent pile-up in the uniform HNM (Fig. 45c) is similar to the highly NT
samples, while the gradient HNM showed a slight increase in the indent size and no visible material
pile-up at the edges of the indenter tip (Fig. 45d). Some details on the deformation underneath the
indenter can be observed in the BF STEM images, including no visible cracking in any of the
samples. In the fully NT structures (Fig. 45e, f), slight deformation and bending of the columnar
grains are observed, as seen previously in NT columnar structure deformation under indentation
[230]. In the HNM samples, the complex network of nanodomains can be observed (Figs. 45g, h),
noting plastic flow in the uniform HNM and shear banding in the gradient HNM.
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Figure 46: (a) DF STEM micrograph of heterogeneous structure with uniform distribution of nanodomains,
highlighting regions of deformation near surface. Regions I (b) and II (c) highlight deformation behavior of sample.
(d) Corresponding EDS maps of entire deformed region, highlighted by dotted gold box.

95

Figure 47: (a) DF STEM micrograph of heterogeneous structure with gradient distribution of nanodomains,
highlighting regions of deformation near surface, with shear bands indicated by the dotted white lines. Regions I (b)
and II (c) highlight deformation behavior of sample. (d) Corresponding EDS maps of entire deformed region,
highlighted by dotted gold box.

Further evaluation of the combined influence of the nanodomains on the deformation of
the HNMs are presented in the STEM micrographs and EDS maps in Figures 46 (uniform HNM)
and 47 (gradient HNM). Each figure provides a DF STEM image (Figs. 46a, 47a), magnified
micrographs of two regions, I and II, (Figs. 46b, c and 47b, c), and EDS maps of the major
constituent elements in Inconel 725 for the entire deformed region (Figs. 46d, 47d). For the
uniform HNM (Fig. 46), a couple of different mechanisms to accommodate plastic deformation
can be observed, including material pile-up on the indent face and plastic flow. Regions I (Fig.
46b) and II (Fig. 46c) highlight compression and rotation of the grains in the direction of the
material pile-up. The plastic flow is emphasized in the EDS maps (Fig. 46d), which show a high
density of M23C6 carbide precipitates near the free surface that rotate and migrate towards the area
of material pile-up. By comparison, the gradient HNM (Fig. 47) features more strain localization
directly underneath the indent, including the formation of two distinct shear bands, highlighted by
the dotted white lines, with compression of the grains at the free surface (Fig. 47b) and minimal
bending of columnar grains away from the indent (Fig. 47c). It can be seen that the plastic zone
96

for the gradient HNM is deeper (~1500 nm) than that of the uniform HNM (~550 nm), manifesting
as reduced material pile-up along the indent edges, less plastic flow [338], and localized
deformation confined to the region directly underneath the indent. Figure 47d highlights the
microstructural integrity, as the EDS maps show that the M23C6 carbide precipitates remain at the
grain boundaries and keep their shape even directly underneath the indenter. Overall, the presence
of nanosized features across all the examined microstructures improved the hardness compared to
their bulk counterparts, although the distribution of the nanodomains is found to have important
consequences on plastic deformation, which can be a useful tool for improving strength-ductility
synergy. Careful consideration must then be given to the distribution of the nanodomains to design
HNMs with desirable mechanical performance.

5.4. Conclusions
In this study, magnetron sputtering was utilized to produce films with two distinct stress
profiles, which influenced microstructural development both in the as deposited and heat-treated
states. Differences in stress due to substrate type contributed to the formation of coarse- or fine-
grained NT structures in the as-sputtered state, and either a uniform or gradient heterogeneous
nanostructured material post-heat treatment, thus leading to four distinct heterogeneous
microstructures. The HNMs featured complex precipitation and abnormal grain growth; however,
the activation process of the ALGs was dependent upon the stress profile. It was also found that
the distribution of nanodomains had important ramifications on mechanical performance and
deformation behavior. Plastic flow and material pile up were identified in the uniform HNM
microstructure, while localized plastic deformation underneath the indent, including a large plastic
zone, shear banding, and limited pile-up were observed in the gradient HNM. The mechanical
testing leveraged in this work provides a foundational understanding on the effect of nanodomain
distributions on mechanical deformation in HNMs. Altogether, magnetron sputtering can be
utilized to develop distinct heterogeneous microstructures with increased complexity, which can
be tailored for desired mechanical performance.

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6. Chapter 6: A surrogate screening method for the development of tailored
additively manufactured microstructures

6.1. Introduction
Inconel Ni-based superalloys are known to be oxidation-corrosion resistant and well suited for
service in highly reactive environments at extreme temperatures and pressures. For example,
Inconel 718, which features high temperature strength, corrosion and creep resistance, and
excellent weldability [339], is highly used in the aerospace industry, making up 30% of the total
weight of modern aircraft engines [340]. However, the high hardness and low thermal conductivity
of Inconel 718 makes conventional machining and forming processes difficult, especially in the
production of complex-shaped components [341]. As a result, there is a clear need for advanced
manufacturing techniques that can more efficiently produce complex-shaped Inconel parts.
A possible method for producing Inconel components with increased geometric complexity is
metal additive manufacturing (AM), where three-dimensional (3D) parts are built layer-by-layer
by rastering a laser or electron beam over powder or wire feedstock directly from a spliced
computer-aided design (CAD) model [342]. However, AM parts are often compromised by a rapid,
inconsistent cooling rate (10
3
-10
7
K/s), bonding and compositional defects, powder contamination,
porosity, anisotropy, and heterogeneity that can occur during the build process or post-process heat
treatments, thereby limiting the quality, reproducibility, and predictability of their mechanical
properties [341, 343-354]. In the case of Inconel 718, these heterogeneities manifest as cracks and
porosity, grain size variation, and precipitation of Nb and Mo-rich Laves phases which can reduce
both strength and ductility [339]. Furthermore, the cooling rate of AM has been shown to cause
residual stresses throughout the thickness of Inconel 718 parts, leading to part distortion and
precipitation of unexpected phases, which can inhibit mechanical performance [355].
The effects of AM processing on the high temperature creep behavior of AM Inconel 718
are of particular concern, as Ni and Ni-based alloys are susceptible to embrittlement via
preferential segregation of S to grain boundaries (GBs) [356, 357] or increased oxidation during
the AM process [358]. To inhibit S embrittlement, reactive elements, such as Mg, can be added to
Ni-based alloys in trace amounts to “tie up” the S before GB segregation occurs [359]. However,
the high vapor pressure of Mg causes it to evaporate during AM processing [360], thereby
removing the barrier for S segregation. The affects caused by AM are emphasized in the work by
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Kassner, et al., which suggested that S embrittlement in AM Inconel alloys during high-
temperature creep testing is attributed to (1) formation of Al2O3 sites due to increased absorption
of oxygen on the powder and (2) lack of a gettering element to tie up the S. As a result, the S
preferentially segregated to the Al2O3 sites, leading to secondary cracking and creep embrittlement
[207]. Accordingly, there is a need to identify reactive elemental additions with low vapor
pressures, such as Zr, Hf, C, or B [361-364], that can effectively tie up the S in AM Inconel [365-
367]. Important consideration must be given to the composition of these novel element additions
to preserve the known mechanical behavior of the alloy. Current efforts to optimize compositional
resolution in AM include high-throughput synthesis techniques by mixing elemental or alloy
powder as they are fed through the rastering beam to develop compositional gradients [368] or
mixing or blending pure elemental powders prior to the build process [369, 370]. However, these
approaches require time and cost intensive powder atomization [371, 372].
A potential alternative surrogate method yet to be explored in AM studies for facilitating
compositional variation in greater detail is magnetron sputtering, a physical vapor deposition
(PVD) technique that can utilizes multiple magnetrons to deposit material from numerous targets,
enhancing control over alloy stoichiometry with high precision [23]. This technique promotes the
ability to screen discrete compositional arrangements, thus allowing for directed alloy
development [113, 297]. It is a highly tunable technique that allows for the deposition of nearly
any element or alloy, tailorable grain sizes and orientations, and control over the microstructure of
the sputtered coating [19, 21, 22, 27, 30, 373-375]. Films can be produced in a matter of hours,
with tunable thicknesses ranging from sub-nanometers up to a millimeter [376-378], providing
sufficient material for substantial microstructural investigation. Magnetron sputtering has seldom
been connected to the field of additive manufacturing, where a few studies have examined their
tandem capabilities, including depositing absorptive coating on reflective feedstock to improve
powder-beam interactions [379], testing of coating adhesion to AM parts [380], and improving
AM part metallization [381]. More recent efforts have coupled sputtering and e-beam remelting to
screen compositionally graded spaces of potential binary alloys to mimic powder bed fusion
microstructures [371]. However, magnetron sputtering on its own could serve as a surrogate for
screening microstructures produced by AM, as it features rapid cooling rates (~10
9
K/s) [27],
columnar grain structures in the as-prepared state, and the formation of residual stress profiles
99

throughout the film thickness [176], which are all characteristics of AM [343-354]. Additionally,
the deployment of post-processing heat treatments can lead the metastable, non-equilibrium as-
sputtered microstructures to an equilibrium state, allowing the resultant microstructures to be
representative of post-processed AM parts [113]. Furthermore, sputtering can be leveraged to
screen elemental additions in Inconel 718 alloys, serving as a rapid experimental model for the
examination of novel AM microstructures and mitigating the need to develop and characterize
custom, atomized powders for future AM alloy development.
In this work, a comparative study is performed to examine how magnetron sputtering can serve
as a surrogate screening tool for AM microstructures. To do so, Inconel 718 films were deposited
under identical sputtering conditions from either an AM target produced by laser powder bed
fusion (L-PBF), or a conventional target synthesized via arc melting. Sputtered films were then
heat treated using the standard ASTM dual-aging treatment for Inconel 718. Additionally, Inconel
718 films were co-sputtered with small concentrations of either pure Zr or Hf to examine their role
on microstructural formation after heat treatment. Extensive microstructural analysis was
performed on all films, followed by Nano secondary ion mass spectrometry (NanoSIMS)
characterization to determine the S behavior with and without the elemental additions. Overall,
this manuscript highlights, for the first time, how magnetron sputtering can be used as a potential
rapid screening method for novel AM microstructures, thereby enhancing the throughput and
deployment of improved AM materials.

6.2. Materials and Methods
Inconel 718 films were deposited via direct current (DC) magnetron sputtering using either an
arc melted Inconel 718 target (Plasmaterials, inc.) or an AM Inconel 718 target (Beamler 3D)
manufactured via laser powder bed fusion using an EOSINT M 290 (EOS GmbH, Germany).
Inconel 718 powder was used for the L-PBF sample preparation with a spherical morphology and
a particle size range of 20 – 55 µm. Stripe type and contour type laser scanning strategies were
used during layering. The stripe angle was rotated 67.5° when layering N layer → (N + 1) layer,
and a bidirectional scanning method was applied. Laser power was set at 285 W (stripes) and 138
W (contour), and the scanning speed was set at 960 mm/s (stripes) and 300 mm/s (contour). L-
PBF was conducted in a 99.995% Ar gas environment with <0.1% Oxygen. Inconel 718 samples
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using both target types were co-sputtered with elemental additions from (99.7%) Zr or Hf targets
(Plasmaterials, inc.). Deposition conditions for all films are provided in the Appendix (Section D,
Table 19). All films were deposited to be ~2 µm thick, measured via an AMBiOS XP-2
Profilometer, onto 25mm Corning Eagle 2000 glass substrates from a working distance of 13 cm.
Deposition rates ranged from 0.13 nm/s for samples without elemental additions to 0.14 nm/s for
samples with Zr or Hf. The substrate stage was heated to 250°C to improve film adhesion to the
substrate. Residual stresses in the as-sputtered state were calculated by Stoney’s equation [202]
and are provided in Table 9. The radius of curvature of the film was determined via profilometry.
Films were heat treated using the standard dual-aging treatment for Inconel 718 via
GSL1100X tube furnace (MTI Corporation) under a vacuum pressure of 7 x 10
-5
Pa. In the
treatment, films are held at 718°C for 8 h, cooled at 55°C/h to 621°C, held for another 8 h, and
then furnace cooled to RT at 5°C/min. Since sputtering forces a solid solution [27], the initial
solution anneal was skipped.
Composition of the as-sputtered samples was measured via scanning electron
microscopy/energy dispersive x-ray spectroscopy (SEM/EDS) (FEI G4 Helios P-FIB UXe) at 20
kV. The nominal compositions of all films are included in Table 8 and are compared to the industry
standard ranges for Inconel 718 in both at% and wt%. Top surface SEM micrographs were
acquired at 5 kV and a current of 0.1 nA by a FEI G4 Helios P-FIB UXe. X-ray diffraction (XRD)
with Cu K α radiation was employed to generate diffractograms over a 2θ range from 30° to 90°
with a step size of 0.01°/sec and a time/step of 0.2/6334 using a Bruker D8 Advance
Diffractometer. Cross-sectional micrographs were examined using transmission electron
microscopy (TEM), performed by a JEOL JEM-2100F with both STEM and EDS capabilities.
TEM lamellae were prepared by the focused ion beam (FIB) method using a FEI G4 Helios P-FIB
UXe. The region of interest was protected from the ion beam by a deposited ~2 μm layer of Pt.
Transmission Kikuchi diffraction (TKD) was obtained using a FEI G4 Helios P-FIB UXe with an
Oxford Symmetry detector. This data was used to observe grain orientation, grain size, and
morphological information and was correlated to STEM images of the samples.
NanoSIMS data was acquired via Cameca NanoSIMS 50L at the California Institute of
Technology. A rastering Cs+ primary beam of +8 keV sputtered the sample sitting at -8 keV to
generate secondary ions. To get rid of possible sample surface contamination, a beam current of
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~360 pA was first used to pre-sputter an area of 15x15 µm for 900 s. The beam current and
rastering area were then reduced to 60 pA and 12x12 µm, respectively, for image collection.
Secondary ions (32S-, 27Al16O-, 48Ti-, 52Cr-, 58Ni- and 90Zr-/93Nb-/160Hf-) of -8 keV were
simultaneously collected with electron multipliers (EMs). The mass spectrometer was set at high
mass resolution conditions to remove possible interferences for the masses of interest. Each image
size was 512x512 pixels, with a beam dwelling time of 2000 ms/pixel. One frame (cycle) of image
acquisition took about 9 minutes. A set of images on each area consisted of 10 to 20 frames. The
acquired images were processed offline with L’IMAGE, an image processing software.

6.3. Results and Discussion
The high temperature strength of Inconel 718 is attributed to precipitation-hardening which is
facilitated from a dual-aging heat treatment, leading to the precipitation of Ni3Nb γ”, Ni3(Al, Ti)
γ’, and carbides [339]. Thus, the concentration of this work is on the heat-treated samples, since it
is anticipated that few if any microstructural differences will be present in as-sputtered state for
films deposited from either target, as both are prepared under the same deposition conditions [46-
53]. In the following sections, a detailed microstructural analysis is presented, where the as-
sputtered microstructures will be noted as such, and the heat-treated samples will be notated as
“Inconel microstructures”. To elucidate on the viability of magnetron sputtering as a surrogate
method for screening AM microstructures, Section 6.3.2 will present a detailed analysis for the
resultant Inconel microstructures observed from both types of sputtering targets while Section
6.3.2.1 directly compares the produced microstructures in this study to representative AM
literature microstructures. The role of novel elemental additions will then be evaluated in Section
6.3.3.

6.3.1. As sputtered microstructures
Films are first evaluated in the as sputtered state to identify their characteristics directly after
deposition due to the Inconel 718 target type. The compositions of the films deposited from both
targets are included in Table 8 and compared to acceptable ranges for Inconel 718 [162]. Figure 1
provides an overview of the as sputtered films, where Figures 48a and 48b are top surface SEM
micrographs and Figure 48c provides X-ray diffractograms for samples deposited from the AM
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(grey) or arc melted (red) target, respectively. Figure 48d is a representative BF STEM cross-
sectional micrograph of the columnar grain structure found in each film with the growth direction
indicated by the black arrow. Both the top surface micrographs and diffractograms highlight
minimal differences between each sample, as they both feature similar texturing, surface
roughness, and a single-phase FCC structure. In the STEM micrograph, the columnar grain
structure generated by the sputtering process can be observed, with nanotwins identified
throughout the grains, as the low stacking fault energy typical of Inconel alloys (< 30 mJ/m
2
) [315]
can contribute to the formation of very fine nanotwins [145, 147]. Overall, the as-sputtered
microstructures are found to be similar to those observed in other magnetron sputtered Inconel
alloys [143, 382]. Thus, the sputtering process leads to similar microstructures due to the identical
processing parameters used during deposition. Thus, it is necessary to leverage the dual-aging heat
treatment on films deposited from each type of target to facilitate the formation of representative
AM Inconel 718 microstructures.

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Figure 48: As-sputtered microstructural characterization of films without elemental additions. (a, b) top surface SEM
micrographs with border color corresponding to (c) X-ray diffractograms for samples deposited from the arc melted
(red) or AM (grey) Inconel 718 targets. (d) Representative BF STEM micrograph of both samples in the as-sputtered
state, with growth direction indicated by the black arrow.

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Table 8: Composition of samples in at. % (wt. %). Composition ranges for standard Inconel 718 is provided for
reference [162].
Sample Ni Cr Fe Nb Mo Ti Al Zr Hf
AM Inc718
50.3
(51.1)
22.8
(20.5)
18.5
(17.9)
3.1
(5.0)
2.2
(3.6)
1.2
(1.0)
1.8
(0.9)
- -
AM Inc718
+ Zr
50.0
(50.1)
21.7
(19.3)
18.0
(17.2)
3.2
(5.2)
2.1
(3.4)
1.3
(1.1)
1.8
(0.8)
1.9
(2.9)
-
AM Inc718
+ Hf
50.5
(49.4)
21.1
(18.3)
17.7
(16.5)
3.3
(5.1)
2.1
(3.4)
1.2
(1.0)
1.7
(0.7)
-
1.9
(5.6)
Arc Melted
Inc718
52.5
(53.3)
21.2
(19.1)
17.7
(17.2)
3.2
(5.2)
2.0
(3.4)
1.0
(0.8)
2.2
(1.0)
- -
Arc Melted
Inc718 + Zr
51.7
(51.9)
20.6
(18.4)
17.4
(16.7)
3.2
(5.1)
2.0
(3.3)
1.0
(0.8)
2.0
(1.0)
1.9
(3.0)
-
Arc Melted
Inc718 + Hf
51.1
(49.8)
20.5
(17.7)
17.2
(16.0)
3.2
(5.0)
2.0
(3.2)
1.0
(0.8)
2.3
(1.0)
-
2.2
(6.5)
Standard
49.5-
54.5
(50 –
55)
19.0-
23.5
(17 –
21)
Bal*
3.0-
3.4
(4.8–
5.5)
1.7-
2.0
(2.8–
3.3)
0.8-
1.4
(0.7–
1.2)
0.4-
1.7
(0.2–
0.8)
- -

6.3.2. Inconel microstructures without additions
Films were deposited from the arc melted and AM Inconel 718 targets and were heat treated
following standard protocols for Inconel 718. The deposition of films under the same synthesis
parameters but using targets produced by different techniques allows for the examination of subtle
distinctions in the alloy microstructure due to effects of the target processing method. In this case,
sputtering from an AM target grants the ability to capture the compositional effects caused by the
AM process. Comparisons between the microstructures of the two films are provided in Figure 49
where the left column displays the sample deposited from the arc melted target while the right
column highlights the sample from the AM target. Row (a) displays cross-sectional DF STEM
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micrographs with feature size distributions provided inset, and a dotted gold box highlighting the
region where TKD and EDS were performed. The growth direction of each film is indicated by
the black arrow to the left of the micrographs. Row (b) provides TKD patterns and row (c) shows
EDS maps of constitutive elements. Inverse pole figures (IPFs) for the phases identified in the
TKD patterns, including Ni-superalloy, CrC, Ni3Ti, and Ni3Nb, which are provided at the bottom
of the figure. Similarities between both samples include the precipitation of Ni3(Nb, Ti) δ-phase,
as well as an average feature size around 340 – 350 nm. For the sample deposited from the arc
melted target, the grains become partially recrystallized, whereas abnormally large grains (ALGs)
are found in the sample deposited from the AM target. Additionally, CrC are found in the sample
deposited from the AM target, but not in the sample from the arc melted target.

106

Figure 49: Microscopic characterization of Inconel 718 sample sputtered from the (left) arc melted target and (right)
AM target. (a) DF STEM micrograph with distribution of feature sizes inset. Dotted gold box indicates area where
TKD and EDS maps were acquired. Average feature size provided below DF STEM micrograph. (b) TKD pattern for
identified phases. Inverse pole figures provided in bottom of figure. (c) EDS maps of major constituent elements.
White bars in TKD pattern and EDS maps represent 500 nm scale bar.
107

Microstructural features identified in each sample post-heat treatment may be attributed to
their residual stresses in the as-prepared state. In Table 9, which provides residual stress data for
all samples in this study, it can be observed that both sputtered samples have relatively high tensile
stresses in the range of 635 – 880 MPa. High tensile residual stresses have been previously shown
to facilitate the nucleation of both ALGs and enlarged MC carbides (where M = Ti, Ta, Nb, V,
Mo, W, or Cr [365]) in Ni-superalloys, both in sputtered films [143, 382] and in bulk states [166,
177, 355]. The presence of secondary precipitates can also affect the recrystallization behavior of
the material [383], which influences the nucleation of either recrystallized or abnormally large
grains.
Table 9: As deposited residual stress for all samples.
Sample Residual Stress (MPa)
AM Inc718 880
AM Inc718 + Zr 692
AM Inc718 + Hf 556
Arc melted Inc718 637
Arc melted Inc718 + Zr 543
Arc melted Inc718 + Hf 556

Further evaluation of the Inconel microstructures and composition was accomplished by
performing NanoSIMS analysis on the top surface of the films. Specifically, Al2O3 and S
segregation behavior were investigated, as previous work by Kassner, et al. [207] attributed creep
embrittlement in AM Inconel alloys to the presence of these phases at grain boundaries. Figure 50
provides the NanoSIMS results for some of the major constitutive elements of Inconel 718,
including Ni, Cr, Nb, Al + O, Ti, and S. The left column provides data for the sample deposited
from the arc melted target, while the right column is the results from the sample deposited from
the AM target. Here, Al + O does not refer to Al2O3; instead, it provides areas that are rich in both
Al and O. Hot spots, indicated by red, in each of the NanoSIMS maps highlight areas of elemental
segregation and enrichment. For example, the hot spots in the Ni and Nb maps notate the location
of Ni3Nb δ-phase precipitation. In the results for both samples, it can be observed that Al + O and
108

S are uniformly distributed, suggesting that Al2O3 is not present, and that no S segregation is
occurring. These findings are in agreement with the EDS maps for Al in Figure 49, which show
that Al appears to be uniformly distributed in both samples. Altogether, the S is found to not
segregate, as there is no preferential phase or element observed in either film. The evaluation of
the representative Inconel 718 microstructures highlights similarities between samples deposited
from each type of target and the ability of sputtering plus heat treatment as a method of tailoring
microstructural formation. In the following section, similarities between the resultant
microstructures in this work compared to reported AM Inconel 718 microstructures from literature
will be addressed to confirm the surrogate behavior of the sputtering process.

109

Figure 50: NanoSIMS maps for constituent elements in each sample. Left column is the sample deposited from the
arc melted target, while the right column is the sample deposited from the additively manufactured target.
110

6.3.2.1. Comparison to AM Inconel 718 microstructures from literature
Comparisons between the two Inconel microstructures in this work (sputtered + heat treated)
and reported AM Inconel 718 microstructures from literature [355, 384-389] indicate many
similarities. For instance, the residual stress calculated for the samples in this work are within the
range of recorded tensile residual stresses in as-built AM Inconel 718 parts (400 – 800 MPa) [355,
384, 385]. The residual stress profile is important for phase formation during post-processing of
Ni-superalloys, as it has been shown to facilitate the nucleation of unexpected structures outside
of typically expected γ”, γ’, and carbide precipitation [143, 382]. Notably, these stresses cause the
δ-phase to readily form, much earlier than the typical ~100 hours of aging required [323].
Numerous studies on AM Inconel 718 observed the precipitation of δ-phase [355, 386-389],
although the location and morphology of the precipitate is dependent upon initial solution or
homogenization anneals performed at the start of the dual-aging treatment. Since sputtering forces
a solid solution, the Inconel microstructures in this work can be directly compared to studies that
leveraged a solution anneal, where the δ-phase tends to precipitate intragranularly with an acicular
morphology [388, 389]. Notably, the γ” and γ’ strengthening precipitates appear to be suppressed
by the sputtering process, which has been observed in other magnetron sputtered Ni-superalloys
[143, 382]. Furthermore, the presence of residual stresses can facilitate recrystallization of the
grains [389], like those seen in the sample deposited from the arc melted target. With regards to
the NanoSIMS analysis, previous research on AM Inconel alloys have identified Al2O3
precipitation due to increased oxidation of the powder during the powder consolidation process,
leading to creep embrittlement [207, 390, 391] By contrast, no Al2O3 precipitation was identified
in the Inconel microstructures observed in this work, as the high vacuum environment of DC
magnetron sputtering, coupled with conventional pre-sputtering to clean the target before
deposition, reduces the O content compared to AM, thereby inhibiting the formation of Al2O3
phases. Nevertheless, the results from the sputtered films suggest that magnetron sputtering can
achieve similar microstructures to AM, however the manufacturing process for the sputtering
target material can lead to important distinctions in microstructural evolution after heat treatment.

111

6.3.3. Effect of novel elemental additions in Inconel microstructures
Sections 6.3.2 and 6.3.2.1 presented the suitability of magnetron sputtering plus heat
treatment as a representative methodology to screen AM Inconel microstructures with high
compositional resolution. As such, Inconel 718 (arc melted or AM target) films were co-sputtered
with 2 at. % Zr or Hf (Table 8) to examine the effect of these novel elemental additions on the
microstructure with a particular focus on S segregation. A 2 at. % minimum for Zr or Hf content
was due to system limitations, capping the minimum deposition rate of the Zr and Hf targets at
0.01 nm/s and the maximum rate for the Inconel 718 targets at 0.13 nm/s [392, 393]. Zr and Hf
were selected as the elemental additions due to low vapor pressures [361-364], propensity for
reaction with S [365, 394], and ease of sputtering compared to other potential reactive elements,
like C, O, B, P, or N, of which only C and B can be sputtered in non-reactive (RF) processes [19].
In Ni-based alloys, Zr promotes desulfurization at GBs due to insolubility in the Ni matrix and
strengthening precipitates [394], whereas Hf preferentially enters carbides and γ’ precipitates
[365], pulling S away from GBs and preventing GB embrittlement [394]. Although the
concentration of Zr and Hf are higher than typical getter element content in cast or wrought Inconel
718 ( < 1000 ppm) [207, 359], it is anticipated that the behavior of these elements in the Inconel
matrix, such as segregation preferences, will be representative regardless of composition. For
example, increasing Mg content in Al5XXX series alloys results in more pronounced precipitation
of Al3Mg2 ß-phase particles at intergranular sites [395]. Furthermore, the higher concentrations of
Zr and Hf facilitates identification of their preferred sites in the Inconel matrix.
To that end, the effect of Zr or Hf additions are analyzed in Figures 51 and 52 for both types
of Inconel targets, respectively. In each figure, row (a) displays cross-sectional DF STEM
micrographs with feature size distributions provided in the inset, and a dotted gold box highlighting
the region where TKD and EDS were performed. The growth direction of each film is indicated
by the black arrow to the left of the micrographs. Row (b) provides TKD patterns and row (c)
shows EDS maps of constitutive elements. IPFs for the phases identified in the TKD patterns,
including Ni-superalloy, Cr-C, Ni3Ti, and Ni3Nb, are provided at the bottom of each figure. For
samples with Zr additions (Figure 51), significant microstructural differences compared to the
representative Inconel 718 microstructures are identified, including retention of the nanotwinned
columnar grains from the as-sputtered state, limited δ-phase precipitation, segregation of Nb and
112

Zr enriched zones to the GBs, and a decrease in the average feature size from ~345 nm to 83 nm.
The migration behavior of Zr is in line with previously reported trends, as it tends to segregate to
and pin GBs, thereby improving thermal stability in both binary alloys [396, 397] and advanced
engineering materials [365, 398], hence the preservation of the nanotwinned columnar grains. One
major difference between the samples is the size of the Zr-enriched zones, which are ~60 nm or
~90 nm when deposited from the AM target or the arc melted target, respectively. Otherwise, the
microstructural evolution across both samples remains consistent with the addition of Zr. By
contrast, samples with Hf additions (Figure 52) exhibit more microstructural variation due to the
target type. For the sample deposited from the arc melted target, smaller Cr-C precipitates (~114
nm) are identified, coupled with more Ni3(Al, Ti, Nb) sites. For the sample deposited from the AM
target, enlarged, agglomerated Cr-C precipitates (~195 nm) can be observed, leading to a larger
average feature size of 167 nm compared to 146 nm for the sample from the arc melted target. In
both samples, the Ni3(Al, Ti, Nb) sites are found to be enriched with Hf, which has been shown to
preferentially enter these types of precipitates [365]. Compared to the representative Inconel 718
microstructures in Figure 49, the addition of Hf contributes to a 2x decrease in average feature size
and some retention of the nanotwinned columnar grain structures from the as-sputtered state, but
not to the same extent as the addition of Zr. It should be noted that alloying with either Zr or Hf
leads to a slight decrease in the global residual stress state of the films, with tensile stresses in the
range of 540 to 690 MPa (Table 9). Thus, the elemental additions have important ramifications on
microstructural evolution for films deposited from each type of Inconel target.
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Figure 51: Microscopic characterization of Inconel 718 sample with Zr additions sputtered from the (left) arc melted
target and (right) AM target. (a) DF STEM micrograph with distribution of feature sizes inset. Dotted gold box
indicates area where TKD and EDS maps were acquired. Average feature size provided below DF STEM micrograph.
(b) TKD pattern for identified phases. Inverse pole figures provided in bottom of figure. (c) EDS maps of major
constituent elements. White bars in TKD pattern and EDS maps represent 500 nm scale bar.
114

Figure 52: Microscopic characterization of Inconel 718 sample with Hf additions sputtered from the (left) arc melted
target and (right) AM target. (a) DF STEM micrograph with distribution of feature sizes inset. Dotted gold box
indicates area where TKD and EDS maps were acquired. Average feature size provided below DF STEM micrograph.
(b) TKD pattern for identified phases. Inverse pole figures provided in bottom of figure. (c) EDS maps of major
constituent elements. White bars in TKD pattern and EDS maps represent 500 nm scale bar.
The preferred distribution of Zr or Hf in the Inconel matrix are found to be different,
therefore it is critical to determine if and how these elemental additions interact with S. Therefore,
NanoSIMS was performed on the top surface of films containing Zr or Hf deposited from each
115

type of target. Figure 53 provides the NanoSIMS results for some of the major constitutive
elements of Inconel 718 with additions, including Ni, , Ti, Zr or Hf, and S. The top half of the
figure above the dotted black line presents data for samples with Zr additions, while the bottom
half features the results for samples with Hf additions. Rows (a) and (c) are samples deposited
from the arc melted Inconel 718 target, while rows (b) and (d) are those deposited from the AM
target. In row (a), S segregation occurs in areas that are also rich in Zr. Interestingly, this behavior
is not identified in the sample deposited from the AM target in row (b) as S segregation is observed,
but Zr enrichment is not. It is possible that the reduced size of the Zr-enriched zones (~60 nm) in
the sample deposited from the AM target may be reaching the lowest achievable resolution limit
of NanoSIMS (~50nm) [226]. For samples with Hf additions, S segregation can also be observed
in rows (c) and (d); however, these S hot spots appear to be linked to enriched areas in the Ti maps
highlighted by the yellow circles, whereas Hf segregation is not easily identifiable. Notably, the
EDS maps in Fig. 52c indicate that Hf preferentially consolidates to Ti-rich areas, which has been
observed in other Ni-based alloy systems [365]. Furthermore, in Fig. 50, no S segregation was
identified in the Inconel microstructures without additions; thus, it appears that the addition of Hf
contributes to the S segregation to Ti-enriched zones from the NanoSIMS analysis. The low
detection quality of the Hf maps was due to the negative polarity that was leveraged during
NanoSIMS, which was necessary to capture the trace amounts of S (<100 ppm), which
preferentially forms negative ions. Under these conditions, heavier elements with a preference for
forming positive ions, like Hf, are difficult to detect [399]. Nevertheless, the addition of either Zr
or Hf is found to facilitate S segregation behavior suggesting the addition of these elements may
serve as a potential solution for improving high temperature mechanical behavior in AM Inconel
alloys.

116

Figure 53: NanoSIMS maps for constituent elements in samples with Zr (above dotted black line) or Hf (below dotted
black line) additions. Rows (a) and (c) are samples deposited from the arc melted Inconel 718 target while rows (b)
and (d) are those from the AM target. Regions of Ti and S enrichment in samples with Hf additions indicated by
yellow circles.
6.4. Conclusions
Magnetron sputtering coupled with heat treatment is proposed as a surrogate screening method
for developing novel AM Inconel microstructures with high compositional resolution. Samples are
117

sputtered from either an arc melted or AM Inconel 718 target to capture subtle differences in the
microstructure from effects of the target processing method. Due to comparable residual stresses
and precipitation behavior, representative Inconel 718 microstructures produced by the magnetron
sputtering technique were developed, with many similarities to previously observed AM Inconel
materials. Films were then co-sputtered with either Zr or Hf to examine the role of these novel
elemental additions on microstructural evolution and S interactions. While Zr and Hf tend
consolidate in different areas of the microstructure, their additions were found to promote S
segregation behavior. Future work should examine how the segregation of S to different sites in
the microstructure will ultimately influence mechanical performance at elevated temperatures.
Altogether, the methodology proposed in this work can serve as a technique for screening AM
microstructures, which can include additions of both metals and ceramics. Thus, the methodology
is a potential alternative to the development and characterization of custom, atomized powders,
and can accelerate the design, deployment, and development of future AM materials.

118

7. Chapter 7: General Conclusions and Future Research Outlook

Understanding the complex interplay of processing-microstructure relationships is critical
in the design of advanced engineering materials; however, efforts have been limited due to
processing variability. To address these shortcomings, the development of a highly tunable
synthesis technique is necessary to bridge materials design across processing methods. In this
dissertation, magnetron sputtering is highlighted as a tool for transcending previous synthesis-
microstructure design spaces by imposing compositional and microstructural complexity in
nanostructured metallic alloys with high precision. Microstructures are tailored by isolating
processing inputs, including target power, magnetron configuration, residual stresses, and post-
deposition heat treatments to identify the effects of the individual inputs on compositional and
microstructural variation. A multitude of synthesis parameters can then be combined as a
comprehensive processing methodology to investigate microstructural, thermodynamic, and
mechanical trends and phenomena for both bulk and nanoscale materials via representative
microstructural formation.
Compositionally guided materials design is examined in the study of multi-principal
element alloys (MPEAs), where target power and chamber configuration were manipulated to
impart high compositional resolution and discovery. The roles of individual elements, their atomic
characteristics, and compositions on microstructural formation and phase transitions could then be
investigated, with distinct phase transition “zones” from crystalline to amorphous structures
identified. The inclusion of elements like Al and Co promoted ordered, crystalline phase
formation, whereas Ti and Cr contributed to phase instability and amorphous structures. The
configuration of the elements and phase structures were then directly linked to mechanical
properties, as crystalline phases tended to exhibit improved hardness and reduced moduli
compared to their amorphous counterparts. The findings herein emphasize the importance of
composition and atomic characteristics on phase formation, highlighting magnetron sputtering as
a tool for investigating complex compositional spaces.
Non-compositional effects on microstructure were then studied in the development of
heterogeneous Ni-superalloys, where altering the residual stress profile innate to the sputtering
process was leveraged to facilitate the formation of unique nanodomain distributions, both in the
119

as-sputtered state and after heat treatment. By changing the substrate type, distinct residual stress
profiles were developed throughout the film thickness, leading to complex microstructural features
including abnormally large grains, rafted structures, annealing twins, growth twins,
nanocrystalline equiaxed grains, Cr-C, and δ-phase precipitation in either a gradient or uniform
distribution throughout the film thickness. Moreover, the distribution of the structures had
important ramifications on mechanical behavior, as Vickers micro-indentation and
nanoindentation testing indicated that the gradient distribution contributed to strain localization in
the area underneath the indent, but the uniform distribution led to plastic flow and material pile-
up. The study demonstrates how only a single processing input (substrate type) can lead to vastly
distinct stress conditions, thereby influencing the formation of complex microstructures.
After emphasizing the ability of magnetron sputtering to control composition and
microstructure with high precision, compositional variation is combined with the design of
heterogeneous structures to develop a fully comprehensive processing technique that can be
leveraged to screen microstructures typically observed in other synthesis methods. Due to similar
residual stress profiles, cooling rates, and precipitation behavior, magnetron sputtering, in tandem
with post-processing heat treatments, can be used as a surrogate for the development of additively
manufactured (AM) materials, particularly Ni-superalloys. Using the co-sputtering method, low
concentrations of Zr and Hf are added to Inconel 718 to study their influence on S segregation
behavior with the goal of improving mechanical performance at elevated temperatures by reducing
creep embrittlement. It was found that additions of Zr and Hf both act as getters for S in the Inconel
matrix, while also exhibiting significant influence on microstructural evolution. The findings here
serve as a proof-of-principle for the rapid screening of novel compositional variation for AM
purposes, providing an alternative for producing custom, atomized powders, which have extensive
lead times.
While the studies in this dissertation highlight the versatility of magnetron sputtering and
its capability as a tool for screening complex compositional and microstructural spaces, there are
still many unsatisfied questions within the topics of the materials explored. Two ongoing issues in
the field of MPEAs include the broad alloy definition and variability in microstructures across
synthesis techniques. Magnetron sputtering, coupled with post-processing heat treatments, can
potentially resolve each of these outstanding issues. Expansive compositional spaces can be
120

investigated with high precision by leveraging large substrates and substrate masking in a co-
sputtering configuration, yielding hundreds of discrete samples in a single sputtering run [98, 243,
297]. This combinatorial approach, in tandem with high-throughput characterization, including
automated x-ray diffraction, EDS, and mechanical testing, as well as post-processing heat
treatment, can allow for the direct correlation and thorough analysis of the effect of different
alloying elements, their atomic characteristics, and compositions across synthesis techniques,
thereby bridging the current knowledge gap in the field.
In the study on heterogeneous Ni-superalloys, many of the unique nanodomains and their
distributions were attributed to stress states present in each film. Further work should seek to
correlate localized stress data to types of nanodomains that form throughout the film thickness,
either in-situ via multi-beam optical sensor (MOS) systems [308] or post-deposition via x-ray
synchrotron nanodiffraction [191, 400] and ion beam layer removal (ILR) [174] methods, thereby
allowing for tailored heterogeneous microstructural development. It should be noted that both ex-
situ stress analysis techniques require the films to remain on the substrate; therefore, processing
parameters, such as deposition rate, working pressure, and substrate type, biasing, and temperature
[176], must be altered to ensure film adhesion, with a particular emphasis on decreasing the high
tensile residual stresses found within the study. Reducing these stresses will have the added benefit
of making mechanical testing more feasible. While general deformation behavior under
compression is presented in this work, a more thorough evaluation of strength-ductility behavior,
as well as localized mechanical deformation of the unique nanodomains should also be
investigated. Global strength-ductility can be analyzed via micro-tensile testing, whereas the
mechanical behavior of the individual nanodomains can be determined via cross-sectional
nanoindentation. Each of these techniques requires thicker films, which should ultimately reduce
the stress, as outlined in Stoney’s equation [202]. A thorough evaluation of the strength-ductility
behavior of the heterogeneous nanostructured materials (HNMs) in this work will allow for the
comparison to other HNMs, which are renowned for their strength-ductility synergy.
Although magnetron sputtering plus heat treatment was presented as a surrogate screening
tool for AM Ni-superalloys, the true test of the methodology will be extrapolating the results to
future, custom AM components. AM Inconel 718 parts with novel elemental additions should be
subjected to creep testing at elevated temperatures to determine if the additions of Hf or Zr (or
121

both) improve the creep behavior compared to AM Inconel without additions. Moreover, the role
of the location of S segregation should be thoroughly investigated, as the Zr and Hf were found to
consolidate at different areas in the Inconel microstructure. Mechanical and physical behavior in
general, including elastic modulus, strength-ductility behavior, and corrosion resistivity, must also
be evaluated to ensure that the novel elemental additions do not inhibit the known performance of
the alloy.
Overall, this dissertation highlights the versatility of magnetron sputtering for the design
of compositionally and microstructurally complex nanostructured materials. Through
customizable deposition conditions, coupled with post-processing heat treatment, magnetron
sputtering can be leveraged to investigate microstructural, thermodynamic, and mechanical trends
across other synthesis methods. The development of representative microstructures offers the
promise of closing the processing-microstructure-properties-performance loop, thereby facilitating
the discovery, development, and design of compositionally and microstructurally complex
advanced engineering materials.

122

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158

Appendix A. Summary of sputtered samples

This appendix contains tables with the list of films sputtered over the course of the dissertation.
Sample labels with an asterisk are those used for publication. Notation for characterization
performed on the samples are as follows: scanning electron microscopy (SEM), energy dispersive
x-ray spectroscopy (EDS), x-ray diffraction (XRD), scanning transmission electron microscopy
(STEM), transmission Kikuchi diffraction (TKD), Nanoscale secondary ion mass spectrometry
(NanoSIMS), and heat treatment (HT). Table 10 contains samples that were sputtered at Karlsruhe
Institute of Technology (KIT). All other tables contain samples sputtered at USC.

Table 10: AlFeNiTi sputtered samples – Sputtered at KIT
Sample
label
Al
Power
(W)
Fe
Power
(W)
Ni
Power
(W)
Ti
Power
(W)
Ar
Pressure
(mbar)
Working
Disance
(cm)
Total
Thickness
(nm)
sputtering
rate
(nm/sec)
Characterization Notes
SUB-1 250 200 60 250 0.001 28.5 596.1 0.16 XRD, SEM, EDS
"equiaxed"
arrangement
SUB-3 250 200 60 250 0.001 28.5 585.5 0.16 XRD, SEM, EDS
"equiaxed"
arrangement
SUB-4 250 200 60 350 0.001 28.5 658.5 0.18 XRD, SEM, EDS
"HCP"
arrangement
SUB-6 250 200 60 350 0.001 28.5 625.0 0.17 XRD, SEM, EDS
"HCP"
arrangement
SUB-7 250 200 200 250 0.001 28.5 774.9 0.22 XRD, SEM, EDS
"FCC"
arrangement
SUB-8 250 200 200 250 0.001 28.5 n/a n/a XRD, SEM, EDS
"FCC"
arrangement,
vacuum tape
peeled
during
sputtering,
no lip for
thickness
SUB-13 250 200 200 250 0.001 28.5 767.8 0.21 XRD, SEM, EDS
"FCC"
arrangement
SUB-14 250 200 200 250 0.001 28.5 768.4 0.21 XRD, SEM, EDS
"FCC"
arrangement
SUB-10 250 200 60 250 0.001 28.5 1010.0 0.15 n/a
"equiaxed"
arrangement
159

SUB-11 250 200 60 250 0.001 28.5 1010.0 0.15 n/a
"equiaxed"
arrangement
SUB-12 250 200 60 350 0.001 28.5 n/a n/a n/a
"HCP"
arrangement,
scratched in
chamber,
broken upon
removal
SUB-18 250 200 60 350 0.001 28.5 n/a n/a n/a
"HCP"
arrangement,
scratched in
chamber,
broken upon
removal
SUB-15 250 200 200 250 0.001 28.5 n/a n/a n/a
"FCC"
arrangement
SUB-19 250 200 200 250 0.001 28.5 n/a n/a n/a
"FCC"
arrangement,
broke upon
removal
SUB-20 200 200 120 250 0.001 28.5 n/a n/a n/a
modified
equiaxed
arrangement,
broken upon
removal
SUB-24 200 200 120 250 0.001 28.5 n/a n/a n/a
modified
equiaxed
arrangement,
broken upon
removal
SUB-17 200 200 120 250 0.001 28.5 n/a n/a n/a
modified
equiaxed
arrangement,
burned
through Fe
target

Table 11: AlCrFeNiTi sputtered samples
Sample label
Al
Power
(W)
CrFeNi
Power
(W)
Ti
Power
(W)
Ar
Pressure
(mtorr)
Working
Disance
(cm)
Total
Thickness
(nm)
sputtering
rate
(nm/sec)
Characterization Notes
SUB01-top-side01 8 100 50 3 13 1195.8 0.2 SEM
shadowing
effects/inconsistent
uniformity
160

SUB01-btm-side01 8 100 50 3 13 1067.8 0.2 n/a
shadowing
effects/inconsistent
uniformity
SUB01-top-side02 25 100 50 3 13 1279.6 0.3 n/a
shadowing
effects/inconsistent
uniformity
SUB01-btm-side02 25 100 50 3 13 1103.6 0.2
n/a shadowing
effects/inconsistent
uniformity
SUB02-top-side01 45 100 50 3 13 1254.8 0.3
n/a shadowing
effects/inconsistent
uniformity
SUB02-btm-side01 45 100 50 3 13 1296 0.3
n/a shadowing
effects/inconsistent
uniformity
SUB02-top-side02 70 100 50 3 13 1418.8 0.4
n/a shadowing
effects/inconsistent
uniformity
SUB02-btm-side02 70 100 50 3 13 1251.6 0.3
n/a shadowing
effects/inconsistent
uniformity
SUB03-top-side01 5 100 50 3 13 1218.4 0.2 SEM, EDS, XRD
inconsistent
thickness due to
gun positioning
SUB03-btm-side01 5 100 50 3 13 1129 0.2 SEM, EDS, XRD
inconsistent
thickness due to
gun positioning
SUB03-top-side02 18 100 50 3 13 1174 0.2 SEM, EDS
inconsistent
thickness due to
gun positioning
SUB03-btm-side02 18 100 50 3 13 1191.8 0.2 SEM, EDS
inconsistent
thickness due to
gun positioning
SUB04-top-side01 35 100 50 3 13 1224.2 0.3 SEM
inconsistent
thickness due to
gun positioning
SUB04-btm-side01 35 100 50 3 13 1137.2 0.3 SEM, XRD
inconsistent
thickness due to
gun positioning
SUB04-top-side02 55 100 50 3 13 1287.2 0.4 SEM
inconsistent
thickness due to
gun positioning
161

SUB04-btm-side02 55 100 50 3 13 1134.8 0.3 SEM
inconsistent
thickness due to
gun positioning
SUB05-top-side01 5 100 50 3 13 n/a n/a
n/a inconsistent
thickness due to
gun positioning
SUB05-btm-side01 5 100 50 3 13 n/a n/a
n/a inconsistent
thickness due to
gun positioning
SUB10-top-side01 5 100 50 3 13 537.8 0.1
n/a inconsistent
thickness due to
gun positioning
SUB10-btm-side01 5 100 50 3 13 420.8 0.1
n/a inconsistent
thickness due to
gun positioning
SUB10-top-side02 15 100 50 3 13 941.8 0.2
n/a inconsistent
thickness due to
gun positioning
SUB10-btm-side02 15 100 50 3 13 1343 0.2
n/a inconsistent
thickness due to
gun positioning
SUB14-top-side01 5 100 50 3 13 1286.2 0.2 SEM, EDS, XRD
Inconsistent
thickness
SUB14-btm-side01 5 100 50 3 13 1141.6 0.2 SEM, EDS, XRD
Inconsistent
thickness
SUB14-top-side02 20 100 50 3 13 1173.8 0.2 SEM, EDS, XRD
Inconsistent
thickness
SUB14-btm-side02 20 100 50 3 13 1281.8 0.2 SEM, EDS, XRD
Inconsistent
thickness
SUB15-top-side01 40 100 50 3 13 1251.8 0.2 n/a
Inconsistent
thickness
SUB15-btm-side01 40 100 50 3 13 1192.4 0.2 n/a
Inconsistent
thickness
SUB15-top-side02 65 100 50 3 13 825.2 0.2 n/a
CrFeNi target arc
error 25 min into
sputtering
SUB15-btm-side02 65 100 50 3 13 809.6 0.2 n/a
CrFeNi target arc
error 25 min into
sputtering
SUB08-top-side01 40 100 50 3 13 1440.8 0.3 SEM, EDS, XRD
Inconsistent
thickness
SUB08-btm-side01 40 100 50 3 13 1379 0.3 SEM, EDS, XRD
Inconsistent
thickness
162

SUB08-top-side02 65 100 50 3 13 1342.2 0.3 SEM, EDS, XRD
Incorrect
composition
SUB08-btm-side02 65 100 50 3 13 1183.2 0.3 SEM, EDS, XRD
Incorrect
composition
SUB18-top-side01 25 75 15 3 13 1220 0.2
n/a Incorrect
composition
SUB18-btm-side01 25 75 15 3 13 1161.2 0.1
n/a Incorrect
composition
SUB18-top-side02 25 75 45 3 13 1444.4 0.2 SEM, EDS
Incorrect
composition
SUB18-btm-side02 25 75 45 3 13 1514 0.2 SEM, EDS
Incorrect
composition
SUB19-top-side01 25 75 50 3 13 n/a n/a SEM, EDS
broke upon
removal from
chamber
SUB19-btm-side01 25 75 50 3 13 n/a n/a SEM, EDS
broke upon
removal from
chamber
SUB19-top-side02 25 75 80 3 13 n/a n/a SEM, EDS
broke upon
removal from
chamber
SUB19-btm-side02 25 75 80 3 13 n/a n/a SEM, EDS
broke upon
removal from
chamber
SUB20-top-side01 25 75 50 3 13 1275 0.2 SEM, EDS
Incorrect
composition
SUB20-btm-side01 25 75 50 3 13 1344.2 0.2 SEM, EDS
Incorrect
composition
SUB20-top-side02 25 75 80 3 13 1262.6 0.2 SEM, EDS
Incorrect
composition
SUB20-btm-side02 25 75 80 3 13 1347.4 0.2 SEM, EDS
Incorrect
composition
SUB21-top-side01* 25 75 8 3 13 1083.2 0.1
SEM, EDS, XRD,
nanoindentation
S2-5Ti-T
SUB21-btm-side01* 25 75 8 3 13 1040.6 0.1
SEM, EDS, XRD,
nanoindentation
S2-5Ti-B
SUB21-top-side02* 25 75 25 3 13 1022 0.1
SEM, EDS, XRD,
nanoindentation
S2-13Ti-T
SUB21-btm-side02* 25 75 25 3 13 1117.6 0.2
SEM, EDS, XRD,
nanoindentation
S2-13Ti-B
SUB22-top-side01 25 75 50 3 13 1139.4 0.2 SEM, EDS
Composition
outside of scope
SUB22-btm-side01 25 75 50 3 13 1077.4 0.2 SEM, EDS
Composition
outside of scope
163

SUB22-top-side02* 25 75 85 3 13 1117 0.2
SEM, EDS, XRD,
nanoindentation
S2-32Ti-T
SUB22-btm-side02* 25 75 85 3 13 1186.6 0.2
SEM, EDS, XRD,
nanoindentation
s2-32Ti-B
SUB23-top-side01* 5 100 50 3 13 1131.6 0.2
SEM, EDS, XRD,
nanoindentation
S1-5Al-T
SUB23-btm-side01* 5 100 50 3 13 1023.6 0.2
SEM, EDS, XRD,
nanoindentation
S1-5Al-B
SUB23-top-side02* 15 100 50 3 13 951 0.2
SEM, EDS, XRD,
nanoindentation
S1-15Al-T
SUB23-btm-side02* 15 100 50 3 13 1101 0.2
SEM, EDS, XRD,
nanoindentation
S1-15Al-B
SUB24-top-side01 30 100 50 3 13 1082.2 0.2 SEM, EDS
Composition
outside of scope
SUB24-btm-side01 30 100 50 3 13 1059.6 0.2 SEM, EDS
Composition
outside of scope
SUB24-top-side02* 45 100 50 3 13 1004.8 0.2
SEM, EDS, XRD,
nanoindentation
S1-33Al-T
SUB24-btm-side02* 45 100 50 3 13 1086.4 0.2
SEM, EDS, XRD,
nanoindentation
S1-33Al-B
SUB26-top-side01* 25 75 12 3 13 1125 0.1
SEM, EDS, XRD,
nanoindentation
S2-7Ti-T
SUB26-btm-side01* 25 75 12 3 13 1089.6 0.1
SEM, EDS, XRD,
nanoindentation
S2-7Ti-B
SUB26-top-side02 20 75 15 3 13 1058 0.1
SEM, EDS, XRD,
nanoindentation
Composition
outside of scope
SUB26-btm-side02 20 75 15 3 13 1131.6 0.1
SEM, EDS, XRD,
nanoindentation
Composition
outside of scope
SUB35-top-side01 25 75 15 3 13 n/a n/a n/a
inconsistent
thickness
SUB35-btm-side01 25 75 15 3 13 n/a n/a n/a
inconsistent
thickness
SUB36-top-side01* 25 75 15 3 13 1161.4 0.1
SEM, EDS, XRD,
nanoindentation
S2-8Ti-T
SUB36-btm-side01* 25 75 15 3 13 1062.4 0.1
SEM, EDS, XRD,
nanoindentation
S2-8Ti-B

164

Table 12: AlCoFeNiTi sputtered samples
Sample label
Al
Power
(W)
CoFeNi
Power
(W)
Ti
Power
(W)
Ar
Pressure
(mtorr)
Working
Disance
(cm)
Total
Thickness
(nm)
sputtering
rate
(nm/sec)
Characterization Notes
SUB27-top-side01* 20 100 8 3 13 1479.8 0.2
SEM, EDS,
XRD,
nanoindentation
S4-5Ti-T
SUB27-btm-side01* 20 100 8 3 13 1401.4 0.2
SEM, EDS,
XRD,
nanoindentation
S4-5Ti-B
SUB28-top-side01* 20 100 105 3 13 1118.4 0.2
SEM, EDS,
XRD,
nanoindentation
S4-35Ti-T
SUB28-btm-side01* 20 100 105 3 13 1045 0.2
SEM, EDS,
XRD,
nanoindentation
S4-35Ti-B
SUB29-top-side01 5 100 50 3 13 1124 0.2
SEM, EDS,
XRD
Composition
outside of
scope
SUB29-btm-side01 5 100 50 3 13 1023 0.2
SEM, EDS,
XRD
Composition
outside of
scope
SUB30-top-side01* 50 100 50 3 13 1019.2 0.2
SEM, EDS,
XRD,
nanoindentation
S3-30Al-T
SUB30-btm-side01* 50 100 50 3 13 961 0.2
SEM, EDS,
XRD,
nanoindentation
S3-30Al-B
SUB31-top-side01 11 100 50 3 13 1098.2 0.2
SEM, EDS,
XRD
Composition
outside of
scope
SUB31-btm-side01 11 100 50 3 13 999 0.2
SEM, EDS,
XRD
Composition
outside of
scope
SUB32-top-side01* 20 100 22 3 13 1045 0.2
SEM, EDS,
XRD,
nanoindentation
S4-9Ti-T
SUB32-btm-side01* 20 100 22 3 13 967.2 0.2
SEM, EDS,
XRD,
nanoindentation
S4-9Ti-B
SUB33-top-side01* 5 100 50 3 13 1052.5 0.2
SEM, EDS,
XRD,
nanoindentation
S3-5Al-T
165

SUB33-btm-side01* 5 100 50 3 13 993.8 0.2
SEM, EDS,
XRD,
nanoindentation
S3-5Al-B
SUB34-top-side01* 11 100 50 3 13 1130.6 0.2
SEM, EDS,
XRD,
nanoindentation
S3-10Al-T
SUB34-btm-side01* 11 100 50 3 13 1034.8 0.2
SEM, EDS,
XRD,
nanoindentation
S3-10Al-B

Table 13: CoFeNiTi sputtered samples for collaboration with Diana Farkas, Paulo Branicio, and Aoyan Liang
Sample label
CoFeNi
Power
(W)
Ti
Power
(W)
Ar
Pressure
(mtorr)
Working
Disance
(cm)
Total
Thickness
(nm)
sputtering
rate
(nm/sec)
Characterization Notes
CoFeNiTi - 0%
Ti #1
100 0 3 13 1000 0.12 SEM, EDS, XRD
Sputtered on
2” substrate,
delaminated
CoFeNiiTi - 0%
Ti #2*
150 0 3 13 1000 0.19 SEM, EDS, XRD CoFeNiTi 0
CoFeNiTi - 5%
Ti #1
150 13 3 13 1000 0.19 SEM, EDS
Incorrect
composition
CoFeNiTi - 5%
Ti #2*
150 20 3 13 1000 0.19 SEM, EDS, XRD CoFeNiTi 0.16
CoFeNiTi - 10%
Ti #1*
150 35 3 13 1000 0.20 SEM, EDS, XRD CoFeNiTi 0.33
CoFeNiTi - 15%
Ti #1*
150 55 3 13 1000 0.21 SEM, EDS, XRD CoFeNiTi 0.53
CoFeNiTi - 20%
Ti #1*
150 85 3 13 1000 0.22 SEM, EDS, XRD CoFeNiTi 0.75
CoFeNiTi - 25%
Ti #1*
150 110 3 13 1000 0.24 SEM, EDS, XRD CoFeNiTi 0.16
CoFeNiTi - 25%
Ti #2
150 145 3 13 1000 0.26 SEM, EDS
Incorrect
composition

Table 14: CrFeNiTi sputtered samples for collaboration with Diana Farkas, Paulo Branicio, and Aoyan Liang
Sample label
CrFeNi
Power
(W)
Ti
Power
(W)
Ar
Pressure
(mtorr)
Working
Disance
(cm)
Total
Thickness
(nm)
sputtering
rate
(nm/sec)
Characterization Notes
CrFeNiTi – 0% Ti #1* 150 0 3 13 1000 0.18 SEM, EDS CrFeNiTi 0
CrFeNiTi – 5% Ti #1 150 23 3 13 n/a n/a n/a plasma died
CrFeNiTi – 5% Ti #2 150 23 3 13 n/a n/a n/a plasma died
CrFeNiTi – 5% Ti #3 150 23 3 13 n/a n/a n/a plasma died
166

CrFeNiTi – 5% Ti #4 100 15 3 13 1000 0.13 SEM, EDS
Incorrect
composition
CrFeNiTi – 5% Ti #5* 150 21 3 13 1000 0.19 SEM, EDS, XRD CrFeNiTi 0.16
CrFeNiTi – 10% Ti #1 100 26 3 13 n/a n/a n/a plasma died
CrFeNiTi – 10% Ti #2 150 43 3 13 n/a n/a n/a plasma died
CrFeNiTi – 10% Ti #3 150 43 3 13 n/a n/a n/a plasma died
CrFeNiTi – 10% Ti #4 150 43 3 13 n/a n/a n/a plasma died
CrFeNiTi – 10% Ti #5* 150 43 3 13 1000 0.20 SEM, EDS, XRD CrFeNiTi 0.33
CrFeNiTi – 15% Ti #1* 150 64 3 13 1000 0.21 SEM, EDS, XRD CrFeNiTi 0.53
CrFeNiTi – 20% Ti #1* 150 90 3 13 1000 0.22 SEM, EDS, XRD CrFeNiTi 0.75
CrFeNiTi – 25% Ti #1* 150 120 3 13 1000 0.24 SEM, EDS, XRD CrFeNiTi 1
• Tables 11 and 12 provide data for samples in Phase transition zones in compositionally
complex alloy films influenced by Al and Ti content in Surface and Coatings Technology,
424, 127651, (2021) DOI: 10.1016/j.surfcoat.2021.127651.
• Tables 13 and 14 provide data for samples in collaboration with Diana Farkas, Paulo
Branicio, and Aoyan Liang, CoFeNiTix and CrFeNiTix high entropy alloy thin films
microstructure formation in Acta Materialia (In Revision).
• Samples with asterisk in “sample label” column are those to be used in publication with
publication sample name provided in “notes” column.

167

Table 15: Inconel 725 sputtered samples
Sample
substrate
material
Base
Pressure
(torr x
10^-6)
Power
(W)
Ar
Pressure
(mTorr)
Working
Disance
(cm)
heating/
cooling
(⁰C)
Total
Thickness
(nm)
sputtering
rate
(nm/sec)
Characterization Notes
inc725-
001
si <100> 5.8 150 3 13 n/a 1000 0.22 XRD
Test residual
stress due to
substrate
inc725-
002
corning
glass
5.8 150 3 13 n/a 1000 0.22 XRD
Test residual
stress due to
substrate
inc725-
003
si <100> 6.7 1500 2 7.6 n/a 8000 5.8 n/a
sample broke
upon removal
from holder
inc725-
004
corning
glass
6.7 1500 2 7.6 n/a 8000 5.8
XRD,
nanoindentation
Troubleshooting
inc725-
005
si <100> 0.87 150 3 13 n/a 8000 0.22 n/a
sample flaked
off in chamber
inc725-
006
si <100> 0.87 150 3 13 n/a 8000 0.22 nanoindentation
sample flaked
off in chamber
inc725-
007
corning
glass
0.87 150 3 13 n/a 8000 0.22 n/a
sample flaked
off in chamber
inc725-
008
corning
glass
0.87 150 3 13 n/a 8000 0.22 nanoindentation
sample flaked
off in chamber
inc725-
009
si <100> 4.7 1500 2 7.6 16 8000 5.8 n/a
sample flaked
off in chamber
inc725-
010
si <100> 4.6 1500 2 7.6 16 8000 5.8 n/a
substrate broke
due to CTE
inc725-
011
si <100> 4.7 1500 2 7.6 n/a 8000 5.8 n/a
substrate broke
due to CTE
inc725-
012
corning
glass
4.6 1500 2 7.6 16 8000 5.8 n/a
sample flaked
off in chamber
inc725-
013
si <100> 4.7 1500 2 7.6 n/a 8000 5.8
XRD, residual
stress
broke during
nanoindentation
mounting
inc725-
014
si <100> 4.9 1500 2 7.6 n/a 8000 5.8 n/a
sample flaked
off in chamber
inc725-
015
si <100> 4.9 1500 2 7.6 n/a 8000 5.8 n/a
sample flaked
off in chamber
inc725-
016
corning
glass
4.6 1500 2 7.6 n/a 8000 5.8 n/a
sample flaked
off in chamber
inc725-
017
corning
glass
4.6 1500 2 7.6 n/a 8000 5.8 XRD
could only get
residual stress
168

from perp.
Direction
inc725-
018
si <100> 4.3 1500 2 7.6 n/a 8000 5.8 n/a
sample
exploded with
compressed air
inc725-
019
si <100> 4.3 1500 2 7.6 n/a 8000 5.8 n/a
sample
exploded in
profilometer
inc725-
020
corning
glass
4.2 1500 2 7.6 n/a 8000 5.8 n/a
sample flaked
off in chamber
inc725-
021
si <100> 4.2 1500 2 7.6 n/a 8000 5.8 XRD
Test film
adhesion
inc725-
022
si <100> 6.5 1500 2 7.6 n/a 8000 5.8
XRD, TEM
demo at Fischer
Vacuum tape on
front for
mounting.
sample sent to
Thermo-Fisher
to be FIB'd for
TEM demo
inc725-
023
si <100> 6.5 1500 2 7.6 n/a 8000 5.8
SEM, XRD,
PFIB, TEM
Vacuum tape on
front for
mounting
inc725-
024
corning
glass
6.6 1500 2 7.6 n/a 8000 5.8
EDS, SEM,
XRD, PFIB,
TEM, STEM,
HT,
nanoindentation
(Top and CS)
Test effect of no
substrate
cooling on
microstructure
on glass
inc725-
025
corning
glass
6.6 1500 2 7.6 n/a 8000 5.8
EDS, SEM,
XRD
broke in Austria
inc725-
026
si <100> 6.7 1500 2 7.6 16 8000 5.8 XRD
sample peeled
off substrate but
is flat
inc725-
027
si <100> 6.7 1500 2 7.6 16 8000 5.8 XRD Sent to Austria
inc725-
028*
corning
glass
6.5 1500 2 7.6 16 8000 5.8
EDS, SEM,
XRD, PFIB,
TEM, STEM,
HT, TKD
nanoindentation
(top)
AS: fine grained
NT; HT:
gradient HNM
inc725-
029
corning
glass
6.5 1500 2 7.6 16 8000 5.8
EDS, SEM,
XRD
sent to Austria
169

inc725-
030
si <100> 6.5 1500 2 7.6 n/a 8000 5.8
EDS, SEM,
XRD, PFIB,
TEM, STEM,
HT,
nanoindentation
(top)
Test effect of no
substrate
cooling on
microstructure
on Si
inc725-
031
si <100> 6.5 1500 2 7.6 n/a 8000 5.8
EDS, SEM,
XRD
sent to Austria,
broke there
inc725-
032*
si <100> 6.5 1500 2 7.6 16 8000 5.8
EDS, SEM,
XRD, PFIB,
TEM, STEM,
HT, TKD,
nanoindentation
(Top)
AS: coarse
grained NT;
HT: Uniform
HNM
inc725-
033
si <100> 6.5 1500 2 7.6 16 8000 5.8
EDS, SEM,
XRD
sent to Austria,
broke there
inc725-
034a
si <100> 5.6 1500 2 7.6 n/a 8000 5.8 EDS, SEM
Surface
morphology
repeatability
check
inc725-
034b
si <100> 5.6 1500 2 7.6 n/a 8000 5.8 SEM
Surface
morphology
repeatability
check
inc725-
034c
si <100> 5.6 1500 2 7.6 n/a 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
034d
si <100> 5.6 1500 2 7.6 n/a 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
035a
si <100> 6.0 1500 2 7.6 16 8000 5.8 EDS, SEM
Surface
morphology
repeatability
check
inc725-
035b
si <100> 6.0 1500 2 7.6 16 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
035c
si <100> 6.0 1500 2 7.6 16 8000 5.8 n/a
Surface
morphology
170

repeatability
check, peeled
from substrate
inc725-
035d
si <100> 6.0 1500 2 7.6 16 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
036a
corning
glass
6.5 1500 2 7.6 n/a 8000 5.8 EDS, SEM
Surface
morphology
repeatability
check
inc725-
036b
corning
glass
6.5 1500 2 7.6 n/a 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
036c
corning
glass
6.5 1500 2 7.6 n/a 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
036d
corning
glass
6.5 1500 2 7.6 n/a 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
037a
corning
glass
6.5 1500 2 7.6 16 8000 5.8 EDS, SEM
Surface
morphology
repeatability
check
inc725-
037b
corning
glass
6.5 1500 2 7.6 16 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
037c
corning
glass
6.5 1500 2 7.6 16 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
037d
corning
glass
6.5 1500 2 7.6 16 8000 5.8 n/a
Surface
morphology
repeatability
171

check, peeled
from substrate
inc725-
038a
si <100> 6.5 1500 2 7.6 n/a 8000 5.8 EDS, SEM
Surface
morphology
repeatability
check
inc725-
038b
si <100> 6.5 1500 2 7.6 n/a 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
038c
si <100> 6.5 1500 2 7.6 n/a 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
038d
si <100> 6.5 1500 2 7.6 n/a 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
039a
si <100> 6.5 1500 2 7.6 16 8000 5.8 EDS, SEM
Surface
morphology
repeatability
check
inc725-
039b
si <100> 6.5 1500 2 7.6 16 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
039c
si <100> 6.5 1500 2 7.6 16 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
039d
si <100> 6.5 1500 2 7.6 16 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
040a
corning
glass
6.5 1500 2 7.6 16 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
172

inc725-
040b
corning
glass
6.5 1500 2 7.6 16 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
040c
corning
glass
6.5 1500 2 7.6 16 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
040d
corning
glass
6.5 1500 2 7.6 16 n/a 5.8 EDS, SEM
Surface
morphology
repeatability
check
inc725-
041b
corning
glass
6.5 1500 2 7.6 n/a 8000 5.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
041d
corning
glass
6.5 1500 2 7.6 n/a 8000 5.8 EDS, SEM
Surface
morphology
repeatability
check
inc725-
042
corning
glass
6.5 1500 2 7.6 n/a 8000 5.8 EDS, SEM
Surface
morphology
repeatability
check
inc725-
041a
corning
glass
6.5 1500 2 7.6 16 8000 7.8 SEM
Surface
morphology
repeatability
check
inc725-
041c
corning
glass
6.5 1500 2 7.6 16 8000 7.8 EDS, SEM sent to Austria
inc725-
045
corning
glass
6.5 1500 2 7.6 16 8000 7.8 SEM
Surface
morphology
repeatability
check
inc725-
043a
si <100> 6.5 1500 2 7.6 16 8000 7.8 SEM
Surface
morphology
repeatability
check
inc725-
043c
si <100> 6.5 1500 2 7.6 16 8000 7.8 SEM
Surface
morphology
repeatability
check
173

inc725-
047b
si <100> 6.5 1500 2 7.6 16 8000 7.8 SEM
Surface
morphology
repeatability
check
inc725-
047d
si <100> 6.5 1500 2 7.6 16 8000 7.8 SEM
Surface
morphology
repeatability
check
inc725-
047a
si <100> 6.5 1500 2 7.6 16 8000 7.8 EDS, SEM sent to Austria
inc725-
048c
si <100> 6.5 1500 2 7.6 16 8000 7.8 EDS, SEM sent to Austria
inc725-
048b
si <100> 6.5 1500 2 7.6 16 8000 7.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
048d
si <100> 6.5 1500 2 7.6 16 8000 7.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
048a
si <100> 6.5 1500 20 7.6 16 8000 7.8 SEM
Surface
morphology
repeatability
check
inc725-
047c
si <100> 6.5 1500 20 7.6 16 8000 7.8 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
049a
corning
glass
6.5 1500 20 7.6 16 8000 7.8 SEM
Surface
morphology
repeatability
check
inc725-
049c
corning
glass
6.5 1500 20 7.6 16 8000 7.8 SEM
Surface
morphology
repeatability
check
inc725-
051a
si <111> 6.5 1500 2 7.6 16 8000 7.8 EDS, SEM
Surface
morphology
repeatability
check
inc725-
051c
si <111> 6.5 1500 2 7.6 16 8000 7.8 EDS, SEM
Surface
morphology
174

repeatability
check
inc725-
052a
si <211> 6.5 1500 2 7.6 16 8000 7.8 EDS, SEM
Surface
morphology
repeatability
check
inc725-
052c
si <211> 6.5 1500 2 7.6 16 8000 7.8 EDS, SEM
Surface
morphology
repeatability
check
inc725-
053a
si <100> 6.5 1500 2 8.9 16 8000 4.5
EDS, SEM,
PFIB, STEM
Surface
morphology and
cross section
repeatability
check
inc725-
053c
si <100> 6.5 1500 2 8.9 16 8000 4.5 EDS, SEM
Surface
morphology
repeatability
check
inc725-
049b
corning
glass
6.5 1500 2 8.9 16 8000 4.5 EDS, SEM
Surface
morphology
repeatability
check
inc725-
049d
corning
glass
6.5 1500 2 8.9 16 8000 4.5 EDS, SEM
Surface
morphology
repeatability
check
inc725-
051b
si <111> 6.5 1500 2 8.9 16 8000 4.5 SEM
Surface
morphology
repeatability
check
inc725-
051d
si <111> 6.5 1500 2 8.9 16 8000 4.5 SEM
Surface
morphology
repeatability
check
inc725-
052b
si <211> 6.5 1500 2 8.9 16 8000 4.5 SEM
Surface
morphology
repeatability
check
inc725-
052d
si <211> 6.5 1500 2 8.9 16 8000 4.5 SEM
Surface
morphology
repeatability
check
inc725-
053b
si <100> 1.5 1500 2 8.9 16 8000 4.5 SEM
Surface
morphology
175

repeatability
check
inc725-
053d
si <100> 1.5 1500 2 8.9 16 8000 4.5 SEM
Surface
morphology
repeatability
check
inc725-
054
si <100> 1.5 1500 2 8.9 16 8000 4.5 EDS, SEM
Surface
morphology
repeatability
check
inc725-
055a
si <100> 1.3 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
055c
si <100> 1.3 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
055b
si <100> 1.3 1500 2 8.9 16 8000 4.5 SEM
Surface
morphology
repeatability
check
inc725-
055d
si <100> 1.3 1500 2 8.9 16 8000 4.5 EDS, SEM
Surface
morphology
repeatability
check
inc725-
046
corning
glass
1.3 1500 2 8.9 16 8000 4.5 EDS, SEM
Surface
morphology
repeatability
check
inc725-
050a
corning
glass
6.5 1500 2 8.9 16 8000 4.5 SEM
Surface
morphology
repeatability
check
inc725-
050c
corning
glass
6.5 1500 2 8.9 16 8000 4.5 SEM
Surface
morphology
repeatability
check
inc725-
050b
corning
glass
6.5 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
176

inc725-
050d
corning
glass
6.5 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
056a
si <100> 6.5 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
056c
si <100> 6.5 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
057a
corning
glass
6.5 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
057c
corning
glass
6.5 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
056b
si <100> 6.0 1500 2 8.9 16 8000 4.5 EDS, SEM
Surface
morphology
repeatability
check
inc725-
056d
si <100> 6.0 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
057b
corning
glass
6.0 1500 2 8.9 16 8000 4.5 EDS, SEM
Surface
morphology
repeatability
check
inc725-
057d
corning
glass
6.0 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
058a
si <100> 6.5 1500 2 8.9 16 8000 4.5 EDS, SEM
Surface
morphology
177

repeatability
check
inc725-
058b
si <100> 6.5 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
059a
corning
glass
6.5 1500 2 8.9 16 8000 4.5 EDS, SEM
Surface
morphology
repeatability
check
inc725-
059b
corning
glass
6.5 1500 2 8.9 16 8000 4.5 EDS, SEM
Surface
morphology
repeatability
check
inc725-
058c
si <100> 6.5 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
058d
si <100> 6.5 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
059c
corning
glass
6.5 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
059d
corning
glass
6.5 1500 2 8.9 16 8000 4.5 n/a
Surface
morphology
repeatability
check, peeled
from substrate
inc725-
060
corning
glass
1.5 1500 2 7.6 16 1000 5.5 n/a
Residual stress
due to substrate
test – 1 µm
inc725-
061
si <100> 1.5 1500 2 7.6 16 1000 5.5 n/a
Residual stress
due to substrate
test – 1 µm
inc725-
062
corning
glass
6.0 1500 2 7.6 16 4000 5.5 n/a
Residual stress
due to substrate
test – 4 µm
178

inc725-
063
si <100> 6.0 1500 2 7.6 16 4000 5.5 n/a
Residual stress
due to substrate
test – 4 µm
inc725-
064
corning
glass
1.1 1500 2 7.6 16 20000 5.5
HT,
nanoindentation
20 µm film for
nanoindentation
testing at Julich
inc725-
065
si <100> 1.1 1500 2 7.6 16 20000 5.5
HT,
nanoindentation
20 µm film for
nanoindentation
testing at Julich
inc725-
066
corning
glass
1.0 1500 2 7.6 16 1000 5.5 n/a
Residual stress
due to substrate
test – 1 µm
inc725-
067
si <100> 1.0 1500 2 7.6 16 1000 5.5 n/a
Residual stress
due to substrate
test – 1 µm
Inc725-
068
Corning
glass
4.2 1500 2 7.6 16 2000 5.5 n/a
Residual stress
due to substrate
test – 2 µm
Inc725-
069
Si
<100>
4.2 1500 2 7.6 16 2000 5.5 n/a
Residual stress
due to substrate
test – 2 µm

• Table 12 provides data for samples used in Distribution of nanodomains in
heterogeneous Ni-superalloys: Effect on microstructure and mechanical deformation
in Acta Materialia, 252, 118940, (2023) DOI: 10.1016/j.actamat.2023.118940.
• Samples labeled a – d all sputtered during the same run
o Cut into quarters to perform stress evaluation in Austria; flat film-substrate
interface was required
• Samples with asterisk in “sample label” column are those to be used in publication with
publication sample name provided in “notes” column

179

Table 16: Inconel 718 sputtered samples
Sample
Inc718
Power
(W)
Hf
Power
(W)
Zr
Power
(W)
Ar
Pressure
(mTorr)
Working
Disance
(cm)
heating/
cooling
(⁰C)
Total
Thickness
(nm)
sputtering
rate
(nm/sec)
Characterization Notes
AM inc718-
001
95 0 0 5 13 n/a 2000 0.13 n/a Film deadhesion
AM inc718-
002
95 0 0 5 13 100 2000 0.13 n/a Film deadhesion
AM inc718-
003
95 0 0 5 13 100 2000 0.13 n/a Film deadhesion
AM inc718-
004
95 0 0 5 13 250 2000 0.13 n/a
Film shifted
during
deposition
AM inc718-
005*
95 0 0 5 13 250 2000 0.13
SEM, EDS,
XRD, STEM,
TKD, HT
AM Inc718
AM inc718 +
Zr-001*
95 0 3 5 13 250 2000 0.14
SEM, EDS,
XRD, STEM,
TKD, HT
AM Inc718 + Zr
AM inc718-
006
95 0 0 5 13 250 2000 0.13
nanoindentation,
HT
peeled from
substrate after
HT, duplicate
sample sent to
Julich for
nanoindentation
AM inc718 +
Zr-002
95 2 3 5 13 250 2000 0.14 nanoindentation
Duplicate
sample
AM inc718 +
Hf-001
95 2 0 5 13 250 2000 0.14
SEM, EDS,
XRD
contaminated
during HT
AM inc718 +
Hf-002*
95 0 0 5 13 250 2000 0.14
SEM, EDS,
XRD, STEM,
TKD, HT
AM Inc718 + Hf
STD inc718-
001*
84 0 0 5 13 250 2000 0.13
SEM, EDS,
XRD, STEM,
TKD, HT
Arc Melted
Inc718
STD inc718
+ Zr-001*
84 0 3 5 13 250 2000 0.14
SEM, EDS,
XRD, STEM,
TKD, HT
Arc Melted
Inc718 + Zr
STD inc718
+ Hf-001*
84 2 0 5 13 250 2000 0.14
SEM, EDS,
XRD, STEM,
TKD, HT
Arc Melted
Inc718 + Hf
STD inc718-
002
84 0 0 5 13 250 2000 0.13
HT,
nanoindentation
Duplicate
sample for
180

nanoindentation
at Julich
STD inc718-
003
84 0 0 5 13 250 2000 0.13 SEM, STEM
AS
characterization
STD inc718-
004
84 0 0 5 13 250 2000 0.13 nanoindentation
Duplicate
sample for
nanoindentation
at Julich

• Table 16 provides data for samples used in Magnetron sputtering as a surrogate for laser
additive manufacturing: study on Ni-superalloys by D.C. Goodelman, M.E. Kassner, and
A.M. Hodge in Additive Manufacturing (unpublished work)
• Samples with asterisk in “sample label” column are those to be used in publication with
publication sample name provided in “notes” column

181

Appendix B. Supplementary Materials for Chapter 4

Table 17: Sputtering conditions used for each sample run within the AlCrFeNiTi system. Within varied Al samples,
Al power was increased while power provided to other targets was kept constant. Likewise for the varied Ti samples.
AlCrFeNiTi
System Sample Set
Al
Power (W)
Ti
Power (W)
CrFeNi
Power (W)
Working
Pressure
(Pa)
Avg.
Sputtering
Rate
(nm/min)
1
S1-7Al 5 50 100 0.27 10.3
S1-15Al 15 50 100 0.25 10.8
S1-33Al 45 50 100 0.29 13.9
2
S2-5Ti 25 8 75 0.27 8.2
S2-7Ti 25 12 75 0.25 8.2
S2-8Ti 25 15 75 0.29 7.9
S2-13Ti 25 25 75 0.27 9.1
S2-32Ti 25 85 75 0.25 12.8

Table 18: Sputtering conditions used for each sample run within the AlCoFeNiTi system. Within varied Al samples,
Al power was increased while power provided to other targets was kept constant. Likewise for the varied Ti samples.
AlCoFeNiTi
System Sample Set
Al
Power (W)
Ti
Power (W)
CrFeNi
Power (W)
Working
Pressure
(Pa)
Avg.
Sputtering
Rate
(nm/min)
3
S3-5Al 5 50 100 0.23 10.2
S3-10Al 11 50 100 0.24 10.8
S3-30Al 50 50 100 0.24 14.1
4
S4-5Ti 20 8 100 0.24 9.3
S4-9Ti 20 22 100 0.24 10.1
S4-35Ti 20 105 100 0.24 14.4

182

Figure 54: Representative load-displacement curves for sample S1-7Al-B
Figure 55: Representative load-displacement curves for sample S4-5Ti-T
183

Appendix C. Supplementary Materials for Chapter 5
Figure 56: Schematics of representative microstructures with nanoindentation load-displacement curves. Column (a)
is a NT microstructure, column (b) is the uniform HNM microstructure, and column (c) is the gradient HNM
microstructure.

184

Appendix D. Supplementary Materials for Chapter 6
Table 19: Deposition conditions of samples in Chapter 6
Sample
Base
pressure
(Pa x 10
-5
)
Working
Pressure
(Pa)
Inc718
Power
(W)
Zr
Power
(W)
Hf
Power
(W)
Substrate
Temperature
(⁰C)
Deposition
rate
(nm/s)
Thickness
(μm)
AM Inc718 4.9 0.67 95 N/A N/A 250 0.13 ~2
AM Inc 718 +
Zr
5.7 0.67 95 3 N/A 250 0.14 ~2
AM Inc718 +
Hf
8.5 0.67 95 N/A 2 250 0.14 ~2
Arc Melted
Inc718
4.1 0.67 84 N/A N/A 250 0.13 ~2
Arc Melted
Inc718 + Zr
8.0 0.67 84 3 N/A 250 0.14 ~2
Arc Melted
INc718 + Hf
7.7 0.67 84 N/A 2 250 0.14 ~2

Abstract (if available)

Abstract Nanostructured materials have garnered significant attention due to their remarkable properties in a wide variety of applications; however, the appropriate synthesis parameters for improving multifunctionality in these materials are not yet fully understood. Therefore, a particular emphasis must be placed on processing-microstructure relationships to guide the design of nanostructured materials across various synthesis techniques. To do so, the development of widely tailorable processing methods, capable of enhancing control over compositional resolution and representative microstructural formation is crucial. In this dissertation, magnetron sputtering, a physical vapor deposition (PVD) technique, is examined as a tool for designing nanostructured, advanced engineering materials with increased compositional and microstructural complexity with high precision. Deposition conditions are individually examined to identify their influence on alloy development. Compositionally driven phase formation is evaluated within multi-principal element alloys by using co-sputtering techniques, where distinct phase transition zones are identified and correlated to the atomic characteristics of the alloying elements. Non-compositional effects on microstructural formation are then investigated in Ni-superalloys by tailoring residual stresses via the substrate type to induce unique distributions of heterogeneous nanostructures, which are found to have significant influence over the mechanical performance of the alloy. All the controllable parameters of magnetron sputtering are then combined with post-deposition heat treatment to develop a comprehensive processing technique, in which representative microstructures across different synthesis methods can be readily prepared and evaluated, particularly in the screening of additively manufactured Ni-superalloys. Altogether, this dissertation highlights magnetron sputtering as a highly tailorable and versatile synthesis method, which can then be leveraged as a means of understanding complex processing-microstructure relationships in future developments of advanced engineering materials.

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Creator Goodelman, Daniel Charles (author)

Core Title Tailoring compositional and microstructural complexity in nanostructured alloys

School Viterbi School of Engineering

Degree Doctor of Philosophy

Degree Program Mechanical Engineering

Degree Conferral Date 2023-08

Publication Date 01/06/2024

Defense Date 06/27/2023

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag additive manufacturing,heterogeneous nanostructured materials,high entropy alloys,magnetron sputtering,nanotwins,Ni-based superalloys,OAI-PMH Harvest,physical vapor deposition

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Language English

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Advisor Hodge, Andrea M. (committee chair), Branicio, Paulo (committee member), Kassner, Michael E. (committee member), Luhar, Mitul (committee member), Shao, Yu-Tsun (committee member)

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