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- All Subjects: Materials Science
- Genre: Doctoral Dissertation
- Creators: Jiao, Yang
Description
Electromigration, the net atomic diffusion associated with the momentum transfer from electrons moving through a material, is a major cause of device and component failure in microelectronics. The deleterious effects from electromigration rise with increased current density, a parameter that will only continue to increase as our electronic devices get smaller and more compact. Understanding the dynamic diffusional pathways and mechanisms of these electromigration-induced and propagated defects can further our attempts at mitigating these failure modes. This dissertation provides insight into the relationships between these defects and parameters of electric field strength, grain boundary misorientation, grain size, void size, eigenstrain, varied atomic mobilities, and microstructure.First, an existing phase-field model was modified to investigate the various defect modes associated with electromigration in an equiaxed non-columnar microstructure. Of specific interest was the effect of grain boundary misalignment with respect to current flow and the mechanisms responsible for the changes in defect kinetics. Grain size, magnitude of externally applied electric field, and the utilization of locally distinct atomic mobilities were other parameters investigated. Networks of randomly distributed grains, a common microstructure of interconnects, were simulated in both 2- and 3-dimensions displaying the effects of 3-D capillarity on diffusional dynamics.
Also, a numerical model was developed to study the effect of electromigration on void migration and coalescence. Void migration rates were found to be slowed from compressive forces and the nature of the deformation concurrent with migration was examined through the lens of chemical potential. Void migration was also validated with previously reported theoretical explanations. Void coalescence and void budding were investigated and found to be dependent on the magnitude of interfacial energy and electric field strength.
A grasp on the mechanistic pathways of electromigration-induced defect evolution is imperative to the development of reliable electronics, especially as electronic devices continue to miniaturize. This dissertation displays a working understanding of the mechanistic pathways interconnects can fail due to electromigration, as well as provide direction for future research and understanding.
ContributorsFarmer, William McHann (Author) / Ankit, Kumar (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Jiao, Yang (Committee member) / McCue, Ian (Committee member) / Arizona State University (Publisher)
Created2022
Description
Applications such as heat exchangers, surface-based cellular structures, rotating blades, and waveguides rely on thin metal walls as crucial constituent elements of the structure. The design freedom enabled by laser powder bed fusion has led to an interest in exploiting this technology to further the performance of these components, many of which retain their as-built surface morphologies on account of their design complexity. However, there is limited understanding of how and why mechanical properties vary by wall thickness for specimens that are additively manufactured and maintain an as-printed surface finish. Critically, the contributions of microstructure and morphology to the mechanical behavior of thin wall laser powder bed fusion structures have yet to be systematically identified and decoupled. This work focuses on elucidating the room temperature quasi-static tensile and high cycle fatigue properties of as-printed, thin-wall Inconel 718 fabricated using laser powder bed fusion, with the aim of addressing this critical gap in the literature. Wall thicknesses studied range from 0.3 - 2.0 mm, and the effects of Hot Isostatic Pressing are also examined, with sheet metal specimens used as a baseline for comparison. Statistical analyses are conducted to identify the significance of the dependence of properties on wall thickness and Hot Isostatic Pressing, as well as to examine correlations of these properties to section area, porosity, and surface roughness. A thorough microstructural study is complemented with a first-of-its-kind study of surface morphology to decouple their contributions and identify underlying causes for observed changes in mechanical properties. This thesis finds that mechanical properties in the quasi-static and fatigue framework do not see appreciable declines until specimen thickness is under 0.75 mm in thickness. The added Hot Isostatic Pressing heat treatment effectively closed pores, recrystallized the grain structure, and provided a more homogenous microstructure that benefits the modulus, tensile strength, elongation, and fatigue performance at higher stresses. Stress heterogeneities, primarily caused by surface defects, negatively affected the thinner specimens disproportionately. Without the use of the Hot Isostatic Pressing, the grain structure remained much more refined and benefitted the yield strength and fatigue endurance limit.
ContributorsParadise, Paul David (Author) / Bhate, Dhruv (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Azeredo, Bruno (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2022
Description
Microstructure refinement and alloy additions are considered potential routes to increase high temperature performance of existing metallic superalloys used under extreme conditions. Nanocrystalline (NC) Cu-10at%Ta exhibits such improvements over microstructurally unstable NC metals, leading to enhanced creep behavior compared to its coarse-grained (CG) counterparts. However, the low melting point of Cu compared to other FCC metals, e.g., Ni, might lead to an early onset of diffusional creep mechanisms. Thus, this research seeks to study the thermo-mechanical behavior and stability of hierarchical (prepared using arc-melting) and NC (prepared by collaborators through powder pressing and annealing) Ni-Y-Zr alloys where Zr is expected to provide solid solution and grain boundary strengthening in hierarchical and NC alloys, respectively, while Ni-Y and Ni-Zr intermetallic precipitates (IMCs) would provide kinetic stability. Hierarchical alloys had microstructures stable up to 1100 °C with ultrafine eutectic of ~300 nm, dendritic arm spacing of ~10 μm, and grain size ~1-2 mm. Room temperature hardness tests along with uniaxial compression performed at 25 and 600 °C revealed that microhardness and yield strength of hierarchical alloys with small amounts of Y (0.5-1wt%) and Zr (1.5-3 wt%) were comparable to Ni-superalloys, due to the hierarchical microstructure and potential presence of nanoscale IMCs. In contrast, NC alloys of the same composition were found to be twice as hard as the hierarchical alloys. Creep tests at 0.5 homologous temperature showed active Coble creep mechanisms in hierarchical alloys at low stresses with creep rates slower than Fe-based superalloys and dislocation creep mechanisms at higher stresses. Creep in NC alloys at lower stresses was only 20 times faster than hierarchical alloys, with the difference in grain size ranging from 10^3 to 10^6 times at the same temperature. These NC alloys showed enhanced creep properties over other NC metals and are expected to have rates equal to or improved over the CG hierarchical alloys with ECAP processing techniques. Lastly, the in-situ wide-angle x-ray scattering (WAXS) measurements during quasi-static and creep tests implied stresses being carried mostly by the matrix before yielding and in the primary creep stage, respectively, while relaxation was observed in Ni5Zr for both hierarchical and NC alloys. Beyond yielding and in the secondary creep stage, lattice strains reached a steady state, thereby, an equilibrium between plastic strain rates was achieved across different phases, so that deformation reaches a saturation state where strain hardening effects are compensated by recovery mechanisms.
ContributorsSharma, Shruti (Author) / Peralta, Pedro (Thesis advisor) / Alford, Terry (Committee member) / Jiao, Yang (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2022
Description
Intelligent engineering designs require an accurate understanding of material behavior, since any uncertainties or gaps in knowledge must be counterbalanced with heightened factors of safety, leading to overdesign. Therefore, building better structures and pushing the performance of new components requires an improved understanding of the thermomechanical response of advanced materials under service conditions. This dissertation provides fundamental investigations of several advanced materials: thermoset polymers, a common matrix material for fiber-reinforced composites and nanocomposites; aluminum alloy 7075-T6 (AA7075-T6), a high-performance aerospace material; and ceramic matrix composites (CMCs), an advanced composite for extreme-temperature applications. To understand matrix interactions with various interfaces and nanoinclusions at their fundamental scale, the properties of thermoset polymers are studied at the atomistic scale. An improved proximity-based molecular dynamics (MD) technique for modeling the crosslinking of thermoset polymers is carefully established, enabling realistic curing simulations through its ability to dynamically and probabilistically perform complex topology transformations. The proximity-based MD curing methodology is then used to explore damage initiation and the local anisotropic evolution of mechanical properties in thermoset polymers under uniaxial tension with an emphasis on changes in stiffness through a series of tensile loading, unloading, and reloading experiments. Aluminum alloys in aerospace applications often require a fatigue life of over 109 cycles, which is well over the number of cycles that can be practically tested using conventional fatigue testing equipment. In order to study these high-life regimes, a detailed ultrasonic cycle fatigue study is presented for AA7075-T6 under fully reversed tension-compression loading. The geometric sensitivity, frequency effects, size effects, surface roughness effects, and the corresponding failure mechanisms for ultrasonic fatigue across different fatigue regimes are investigated. Finally, because CMCs are utilized in extreme environments, oxidation plays an important role in their degradation. A multiphysics modeling methodology is thus developed to address the complex coupling between oxidation, mechanical stress, and oxygen diffusion in heterogeneous carbon fiber-reinforced CMC microstructures.
ContributorsSchichtel, Jacob (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Ghoshal, Anindya (Committee member) / Huang, Huei-Ping (Committee member) / Jiao, Yang (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2022
Description
Cellular metamaterials arouse broad scientific interests due to the combination of host material and structure together to achieve a wide range of physical properties rarely found in nature. Stochastic foam as one subset has been considered as a competitive candidate for versatile applications including heat exchangers, battery electrodes, automotive, catalyst devices, magnetic shielding, etc. For the engineering of the cellular foam architectures, closed-form models that can be used to predict the mechanical and thermal properties of foams are highly desired especially for the recently developed ultralight weight shellular architectures. Herein, for the first time, a novel packing three-dimensional (3D) hollow pentagonal dodecahedron (HPD) model is proposed to simulate the cellular architecture with hollow struts. An electrochemical deposition process is utilized to manufacture the metallic hollow foam architecture. Mechanical and thermal testing of the as-manufactured foams are carried out to compare with the HPD model. Timoshenko beam theory is utilized to verify and explain the derived power coefficient relation. Our HPD model is proved to accurately capture both the topology and the physical properties of hollow stochastic foam. Understanding how the novel HPD model packing helps break the conventional impression that 3D pentagonal topology cannot fulfill the space as a representative volume element. Moreover, the developed HPD model can predict the mechanical and thermal properties of the manufactured hollow metallic foams and elucidating of how the inevitable manufacturing defects affect the physical properties of the hollow metallic foams. Despite of the macro-scale stochastic foam architecture, nano gradient gyroid lattices are studied using Molecular Dynamics (MD) simulation. The simulation result reveals that, unlike homogeneous architecture, gradient gyroid not only shows novel layer-by-layer deformation behavior, but also processes significantly better energy absorption ability. The deformation behavior and energy absorption are predictable and designable, which demonstrate its highly programmable potential.
ContributorsDai, Rui (Author) / Nian, Qiong (Thesis advisor) / Jiao, Yang (Committee member) / Kwon, Beomjin (Committee member) / Liu, Yongming (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2021
Description
Phase-field (PF) models are one of the most powerful tools to simulate microstructural evolution in metallic materials, polymers, and ceramics. However, existing PF approaches rely on rigorous mathematical model development, sophisticated numerical schemes, and high-performance computing for accuracy. Although recently developed surrogate microstructure models employ deep-learning techniques and reconstruction of microstructures from lower-dimensional data, their accuracy is fairly limited as spatio-temporal information is lost in the pursuit of dimensional reduction. Given these limitations, a novel data-driven emulator (DDE) for extrapolation prediction of microstructural evolution is presented, which combines an image-based convolutional and recurrent neural network (CRNN) with tensor decomposition, while leveraging previously obtained PF datasets for training. To assess the robustness of DDE, the emulation sequence and the scaling behavior with phase-field simulations for several noisy initial states are compared. In conclusion, the effectiveness of the microstructure emulation technique is explored in the context of accelerating runtime, along with an emphasis on its trade-off with accuracy.Meanwhile, an interpolation DDE has also been tested, which is based on obtaining
a low-dimensional representation of the microstructures via tensor decomposition and subsequently predicting the microstructure evolution in the low-dimensional space using Gaussian process regression (GPR). Once the microstructure predictions are obtained in the low-dimensional space, a hybrid input-output phase retrieval algorithm will be employed to reconstruct the microstructures. As proof of concept, the results on microstructure prediction for spinodal decomposition are presented, although the method itself is agnostic of the material parameters. Results show that GPR-based DDE model are able to predict microstructure evolution sequences that closely resemble the true microstructures (average normalized mean square of 6.78 × 10−7) at time scales half of that employed in obtaining training data. This data-driven
microstructure emulator opens new avenues to predict the microstructural evolution by leveraging phase-field simulations and physical experimentation where the time resolution is often quite large due to limited resources and physical constraints, such as the phase coarsening experiments previously performed in microgravity.
Future work will also be discussed and demonstrate the intended utilization of these two approaches for 3D microstructure prediction through their combined application.
ContributorsWu, Peichen (Author) / Ankit, Kumar (Thesis advisor) / Iquebal, Ashif (Committee member) / Jiao, Yang (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2024
Description
Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures or processing settings. While optimization techniques have mature applications to a large range of engineering systems, their application to material design meets unique challenges due to the high dimensionality of microstructures and the high costs in computing process-structure-property (PSP) mappings. The key to addressing these challenges is the learning of material representations and predictive PSP mappings while managing a small data acquisition budget. This dissertation thus focuses on developing learning mechanisms that leverage context-specific meta-data and physics-based theories. Two research tasks will be conducted: In the first, we develop a statistical generative model that learns to characterize high-dimensional microstructure samples using low-dimensional features. We improve the data efficiency of a variational autoencoder by introducing a morphology loss to the training. We demonstrate that the resultant microstructure generator is morphology-aware when trained on a small set of material samples, and can effectively constrain the microstructure space during material design. In the second task, we investigate an active learning mechanism where new samples are acquired based on their violation to a theory-driven constraint on the physics-based model. We demonstrate using a topology optimization case that while data acquisition through the physics-based model is often expensive (e.g., obtaining microstructures through simulation or optimization processes), the evaluation of the constraint can be far more affordable (e.g., checking whether a solution is optimal or equilibrium). We show that this theory-driven learning algorithm can lead to much improved learning efficiency and generalization performance when such constraints can be derived. The outcomes of this research is a better understanding of how physics knowledge about material systems can be integrated into machine learning frameworks, in order to achieve more cost-effective and reliable learning of material representations and predictive models, which are essential to accelerate computational material design.
ContributorsCang, Ruijin (Author) / Ren, Yi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2018
Description
Collective cell migration in the 3D fibrous extracellular matrix (ECM) is crucial to many physiological and pathological processes such as tissue regeneration, immune response and cancer progression. A migrating cell also generates active pulling forces, which are transmitted to the ECM fibers via focal adhesion complexes. Such active forces consistently remodel the local ECM (e.g., by re-orienting the collagen fibers, forming fiber bundles and increasing the local stiffness of ECM), leading to a dynamically evolving force network in the system that in turn regulates the collective migration of cells.
In this work, this novel mechanotaxis mechanism is investigated, i.e., the role of the ECM mediated active cellular force propagation in coordinating collective cell migration via computational modeling and simulations. The work mainly includes two components: (i) microstructure and micromechanics modeling of cellularized ECM (collagen) networks and (ii) modeling collective cell migration and self-organization in 3D ECM. For ECM modeling, a procedure for generating realizations of highly heterogeneous 3D collagen networks with prescribed microstructural statistics via stochastic optimization is devised. Analysis shows that oriented fibers can significantly enhance long-range force transmission in the network. For modeling collective migratory behaviors of the cells, a minimal active-particle-on-network (APN) model is developed, in which reveals a dynamic transition in the system as the particle number density ρ increases beyond a critical value ρc, from an absorbing state in which the particles segregate into small isolated stationary clusters, to a dynamic state in which the majority of the particles join in a single large cluster undergone constant dynamic reorganization. The results, which are consistent with independent experimental results, suggest a robust mechanism based on ECM-mediated mechanical coupling for collective cell behaviors in 3D ECM.
For the future plan, further substantiate the minimal cell migration model by incorporating more detailed cell-ECM interactions and relevant sub-cellular mechanisms is needed, as well as further investigation of the effects of fiber alignment, ECM mechanical properties and externally applied mechanical cues on collective migration dynamics.
In this work, this novel mechanotaxis mechanism is investigated, i.e., the role of the ECM mediated active cellular force propagation in coordinating collective cell migration via computational modeling and simulations. The work mainly includes two components: (i) microstructure and micromechanics modeling of cellularized ECM (collagen) networks and (ii) modeling collective cell migration and self-organization in 3D ECM. For ECM modeling, a procedure for generating realizations of highly heterogeneous 3D collagen networks with prescribed microstructural statistics via stochastic optimization is devised. Analysis shows that oriented fibers can significantly enhance long-range force transmission in the network. For modeling collective migratory behaviors of the cells, a minimal active-particle-on-network (APN) model is developed, in which reveals a dynamic transition in the system as the particle number density ρ increases beyond a critical value ρc, from an absorbing state in which the particles segregate into small isolated stationary clusters, to a dynamic state in which the majority of the particles join in a single large cluster undergone constant dynamic reorganization. The results, which are consistent with independent experimental results, suggest a robust mechanism based on ECM-mediated mechanical coupling for collective cell behaviors in 3D ECM.
For the future plan, further substantiate the minimal cell migration model by incorporating more detailed cell-ECM interactions and relevant sub-cellular mechanisms is needed, as well as further investigation of the effects of fiber alignment, ECM mechanical properties and externally applied mechanical cues on collective migration dynamics.
ContributorsNan, Hanqing (Author) / Jiao, Yang (Thesis advisor) / Alford, Terry (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2019
Description
Stress corrosion cracking (SCC) is a materials degradation phenomena resulting from a combination of stress and a corrosive environment. Among the alphabet soup of proposed mechanism of SCC the most important are film-rupture, film-induced cleavage and hydrogen embrittlement.
This work examines various aspects of film-induced cleavage in gold alloys for which the operation of hydrogen embrittlement processes can be strictly ruled out on thermodynamic grounds. This is so because in such alloys SCC occurs under electrochemical conditions within which water is stable to hydrogen gas evolution. The alloy system examined in this work is AgAu since the corrosion processes in this system occur by a dealloying mechanism that results in the formation of nanoporous gold. The physics behind the dealloying process as well as the resulting formation of nanoporous gold is today well understood.
Two important aspects of the film-induced cleavage mechanism are examined in this work: dynamic fracture in monolithic nanoporous gold and crack injection. In crack injection there is a finite thickness dealloyed layer formed on a AgAu alloy sample and the question of whether or not a crack that nucleates within this layer can travel for some finite distance into the un-corroded parent phase alloy is addressed. Dynamic fracture tests were performed on single edge-notched monolithic nanoporous gold samples as well as “infinite strip” sample configurations for which the stress intensity remains constant over a significant portion of the crack length. High-speed photography was used to measure the crack velocity. In the dynamic fracture experiments cracks were observed to travel at speeds as large as 270 m/s corresponding to about 68% of the Raleigh wave velocity. Crack injection experiments were performed on single crystal Ag77Au23, polycrystalline Ag72Au28 and pure gold, all of which had thin nanoporous gold layers on the surface of samples. Through-thickness fracture was seen in both the single crystal and polycrystalline samples and there was an indication of ~ 1 μm injected cracks into pure gold. These results have important implications for the operation of the film-induced cleavage mechanism and represent a first step in the development of a fundamental model of SCC.
This work examines various aspects of film-induced cleavage in gold alloys for which the operation of hydrogen embrittlement processes can be strictly ruled out on thermodynamic grounds. This is so because in such alloys SCC occurs under electrochemical conditions within which water is stable to hydrogen gas evolution. The alloy system examined in this work is AgAu since the corrosion processes in this system occur by a dealloying mechanism that results in the formation of nanoporous gold. The physics behind the dealloying process as well as the resulting formation of nanoporous gold is today well understood.
Two important aspects of the film-induced cleavage mechanism are examined in this work: dynamic fracture in monolithic nanoporous gold and crack injection. In crack injection there is a finite thickness dealloyed layer formed on a AgAu alloy sample and the question of whether or not a crack that nucleates within this layer can travel for some finite distance into the un-corroded parent phase alloy is addressed. Dynamic fracture tests were performed on single edge-notched monolithic nanoporous gold samples as well as “infinite strip” sample configurations for which the stress intensity remains constant over a significant portion of the crack length. High-speed photography was used to measure the crack velocity. In the dynamic fracture experiments cracks were observed to travel at speeds as large as 270 m/s corresponding to about 68% of the Raleigh wave velocity. Crack injection experiments were performed on single crystal Ag77Au23, polycrystalline Ag72Au28 and pure gold, all of which had thin nanoporous gold layers on the surface of samples. Through-thickness fracture was seen in both the single crystal and polycrystalline samples and there was an indication of ~ 1 μm injected cracks into pure gold. These results have important implications for the operation of the film-induced cleavage mechanism and represent a first step in the development of a fundamental model of SCC.
ContributorsChen, Xiying (Author) / Sieradzki, Karl (Thesis advisor) / Jiao, Yang (Committee member) / Oswald, Jay (Committee member) / Crozier, Peter (Committee member) / Peralta, Pedro (Committee member) / Arizona State University (Publisher)
Created2016
Description
Nanocrystalline (NC) materials experience inherent microstructural instability when exposed to elevated temperature, deformation rates or loads over long periods of time which limits its applications as well as processing. The instability arises due to the predominance of grain boundary (GB) diffusional processes which hastens coarsening. This dissertation aims to provide a solution for the very first time, through the development and characterization of a bulk NC alloy system. The NC-Cu-Ta discussed here offers exceptional thermal stability in addition to superior strength and creep resistance. The systematic study of the behavior of this material will pave the way for future development of NC materials with a multitude of optimized properties for extreme applications.
In-situ and ex-situ TEM characterization, multiple strain-rate compression testing and atomistic modeling were employed to investigate the behavior of NC-Cu-Ta under intense heating, stress/strain-rate and creep conditions. Results reveal, that temperature influences the misfit strain, leading to a significant change in flow stress, despite which (strength) remains greater than all known NC metals. Further, this alloy was found to achieve and retain strengths which were over two orders of magnitude higher than most NC metals under elevated temperature conditions. Dislocation-based slip was found to predominate at elevated temperatures for both high- and low-strain rate testing whereas twinning was favored during low temperature high-strain rate testing. The solute concentration was also found to play a role in dictating the deformation where heterogeneous twinnability was found to decrease with an increase in Ta concentration.
A paradigm-shift in the creep response of NC-materials with unprecedented property combinations is also reported, i.e., high strength with extremely high temperature creep resistance (6-8 orders higher than other NC materials), in this NC-Cu-Ta-alloy. The unique combination of properties in these NC-alloys is achieved through a processing route that creates distinct GB-pinning nanoclusters of the solute that favor kinetic stability of grains.
Overall, this dissertation provides an understanding of the mechanical response of a stable alloy system to extreme conditions, which was previously unattainable, and a perspective on the design of a new class of NC alloys exhibiting a multitude of optimized high temperature properties.
In-situ and ex-situ TEM characterization, multiple strain-rate compression testing and atomistic modeling were employed to investigate the behavior of NC-Cu-Ta under intense heating, stress/strain-rate and creep conditions. Results reveal, that temperature influences the misfit strain, leading to a significant change in flow stress, despite which (strength) remains greater than all known NC metals. Further, this alloy was found to achieve and retain strengths which were over two orders of magnitude higher than most NC metals under elevated temperature conditions. Dislocation-based slip was found to predominate at elevated temperatures for both high- and low-strain rate testing whereas twinning was favored during low temperature high-strain rate testing. The solute concentration was also found to play a role in dictating the deformation where heterogeneous twinnability was found to decrease with an increase in Ta concentration.
A paradigm-shift in the creep response of NC-materials with unprecedented property combinations is also reported, i.e., high strength with extremely high temperature creep resistance (6-8 orders higher than other NC materials), in this NC-Cu-Ta-alloy. The unique combination of properties in these NC-alloys is achieved through a processing route that creates distinct GB-pinning nanoclusters of the solute that favor kinetic stability of grains.
Overall, this dissertation provides an understanding of the mechanical response of a stable alloy system to extreme conditions, which was previously unattainable, and a perspective on the design of a new class of NC alloys exhibiting a multitude of optimized high temperature properties.
ContributorsRajagopalan, Mansa (Author) / Solanki, Kiran N. (Thesis advisor) / Alford, Terry L. (Committee member) / Jiao, Yang (Committee member) / Darling, Kris A. (Committee member) / Arizona State University (Publisher)
Created2016