|About this Abstract
||2020 TMS Annual Meeting & Exhibition
||Algorithm Development in Materials Science and Engineering
|| A First Principles Multi-Cell Monte Carlo Method for Phase Prediction
||You Rao, Changning Niu, Wolfgang Windl, Maryam Ghazisaeidi
|On-Site Speaker (Planned)
The importance of phase prediction lies not only in the understanding of basic thermodynamics, but also in the development of new materials. This has been a challenging problem due to the innate complexity, especially for multicomponent systems whose phase diagrams have not been established. The existing methods are either limited to binary systems or not applicable to crystalline solids at all. Here we present a new multicell Monte Carlo method based on first principles where the coexisting phases are represented by parallel supercells and free concentration search is achieved via a flip move. We first show that this method works for known miscible and immiscible systems as benchmarks and then we show that it successfully predicts the phase separation of a quaternary high entropy alloy as observed in experiments. Finally, we show that it can also work for semiconductors and intermetallics with appropriate modifiers.
||Planned: Supplemental Proceedings volume