Gouws, Xander Andrew2025-09-052025-09-052025-09-052025-08-06https://hdl.handle.net/10012/22344The simulation of solid-state electrolytes (SSEs) has allows researchers to directly observe the migration paths of lithium ions, and so has played a pivotal role in elucidating the mechanisms of ionic conduction. Performing these simulations requires three steps: Structure determination, simulation, and analysis. Here, we have developed and tested new computational methods to address key challenges in two of these steps. First, we develop a gradient-based optimization method for determining the structures of amorphous materials from total scattering data. Unlike traditional reverse Monte Carlo approaches that rely on random atomic movements and suffer from slow convergence, our gradient-based method moves atoms to directly minimize the chi-squared goodness-of-fit and potential energy. Our approach was tested on amorphous silicon and a nickel--niobium metallic glass. Convergence was achieved in on the order of 5,000 steps, which is approximately one hundred times faster than existing hybrid Monte Carlo methods. Then, we introduce a method for detecting ion hopping events in SSEs without prior knowledge of site locations. This may be useful when simulating i) new materials, for which the positions of all lithium occupancy sites may be unknown, ii) structural changes (e.g. doping) that introduce local strains that shift site positions, or iii) amorphous materials, where lithium sites may be unknown prior to simulation. Testing our method on Li6PS5Cl and its BH4-doped variant, we recover the cage-forming nature of lithium sites in argyrodite structures, and find that the correlation factor for hops between cages is greater than one, indicating a forward-bias for intercage hops.enMaster Thesis