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Physical vapor deposition (PVD) of phase-separating multicomponent alloy films generates a rich variety of unique self-organized nanoscale morphologies. However, an understanding of how the different material and process parameters influence the formation of these nanostructures is limited. My dissertation aims to bridge this gap by developing phase-field models that can predict an entire spectrum of nanostructures as a function of processing conditions and composition in multicomponent alloys under a set of material-specific constraints. Firstly, I developed a numerical model to simulate nanoscale phase separation in codeposited immiscible binary alloy films. An investigation on the influence of deposition rates, phase-fraction, and temperature, on the evolution of self-assembled nanostructures yielded many characteristic patterns, including well-known morphologies such as the lateral and vertical concentration modulations, as well as some previously undocumented variants. I also simulated phase-separation in ternary alloyed PVD films, and studied the influence of deposition rate and composition on the evolution of self-assembled nanostructures, and recorded many novel nanoscale morphologies. I then sought to understand the role of material properties such as elastic misfit due to lattice mismatch between phases, grain boundaries formed in polycrystalline films, and the interplay of interphase and surface boundaries at the film surface. To this end, I developed phase-field models of binary PVD film deposition that incorporated these constraints and studied their role in altering the temporal and spatial characteristics of the evolving morphologies. I also investigated the formation of surface hillocks and the role of surface and interfacial energies in their evolution. By studying the change in total free energy across the different deposition models, I established that, in addition to influencing the temporal and spatial characteristics of nanoscale structures in the films, this quantity is also responsible for driving morphological transitions as the rate of deposition is increased. Insights gained from this computational study will demonstrate the viability of these models in predicting experimentally observed morphologies and form a basis for understanding the various factors involved in driving phase-separation and morphological transitions. In addition, morphology maps will serve as templates for developing new pathways for morphology control in the manufacturing of PVD alloy films.
ContributorsRaghavan, Rahul (Author) / Ankit, Kumar (Thesis advisor) / Rajagopalan, Jagannathan (Committee member) / Mushongera, Leslie T (Committee member) / Arizona State University (Publisher)
Created2021