|About this Abstract
||2021 TMS Annual Meeting & Exhibition
||Hume-Rothery Symposium: Accelerated Measurements and Predictions of Thermodynamics and Kinetics for Materials Design and Discovery
||Multi-cell Monte Carlo Method for Phase Prediction
||Maryam Ghazisaeidi, You Rao, Edwin Antillon, changning Niu, Wolfgang Windl
|On-Site Speaker (Planned)
We propose a Multi-Cell Monte Carlo algorithm, or (MC)^2, for predicting stable phases in chemically complex crystalline systems. This algorithm takes advantage of multiple cells to represent possible phases while eliminating the size and concentration restrictions in their previous counterparts. Free atomic transfer among cells is achieved via the application of the lever rule, where an assigned molar ratio virtually controls the percentage of each cell in the overall simulation, making (MC)^2 the first successful algorithm for simulating phase coexistence in crystalline solids. During the application of this method, all energies are directly computed via density functional theory calculations. We test the method by successful prediction of the stable phases of known binary systems. We then apply the method to a quaternary high-entropy alloy. The method is particularly powerful in predicting stable phases of multicomponent systems, for which phase diagrams do not exist.