Multi-cell Monte Carlo method for phase prediction

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 the previous counterparts. Fr...

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Bibliographic Details
Published in:npj computational materials 2019-12, Vol.5 (1), p.1-5, Article 120
Main Authors: Niu, Changning, Rao, You, Windl, Wolfgang, Ghazisaeidi, Maryam
Format: Article
Language:English
Subjects:
639/301/1034/1035
639/301/1034/1037
Algorithms
Atomistic models
Characterization and Evaluation of Materials
Chemistry and Materials Science
Computational Intelligence
Computational methods
MATERIALS SCIENCE
Mathematical and Computational Engineering
Mathematical and Computational Physics
Mathematical Modeling and Industrial Mathematics
Monte Carlo simulation
Theoretical
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Summary: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 the 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.
ISSN:2057-3960
2057-3960
DOI:10.1038/s41524-019-0259-z