Date of Graduation
Eberly College of Arts and Sciences
Physics and Astronomy
Due to increased availability and power of computational resources over the past few decades, prediction and design of novel materials using computational methods has become feasible. Simulation of material systems has become vital to the further realization of novel material systems. In order to ascertain physical properties, accurate determination and identification of stable crystalline structures is necessary. Additionally, further identification of novel properties, such as magnetic moments or orbital occupation, is necessary to further realize this goal. Global search methods provide a path to accurate prediction of these properties. In this dissertation, the Firefly algorithm and minima hopping methods are presented. The Firefly algorithm is applied to two problems: Magnetic moment orientation optimization and orbital occupation optimization. For the first, three noncollinear systems investigated: NiF2, a weak ferromagnet, and Mn3Pt and the molecular system (MnIV )3O4L4(H2O) , where L = N ,N-bis(methylene)-Z-1,2-ethenediamine, both of which display frustration. For the problem of orbital occupation, UO2 , an oxide, and KCoF3 , a perovskite-like antiferromagnet are investigated to show that FA works equally-well for d and f electron systems. The minima hopping method is applied to the problem of structural search in the binary system NiTi. The convex hull is constructed from this search. From this, results are compared to those previously reported.
Payne, Adam J., "Application of Global Search Methods to Materials Prediction and Design" (2019). Graduate Theses, Dissertations, and Problem Reports. 7377.