GAASP: Genetic Algorithm-Based Atomistic Sampling Protocol for High-Entropy Materials
نویسندگان
چکیده
High-entropy materials are composed of multiple elements on comparatively simpler lattices. Due to the multi-component nature such materials, atomic-scale sampling is computationally expensive due combinatorial complexity. This study proposes a genetic algorithm-based methodology for complex chemically disordered materials. Genetic Algorithm-based Atomistic Sampling Protocol (GAASP) variants can generate low as well high-energy structures. GAASP low-energy variant in conjugation with metropolis criteria avoids premature convergence ensures detailed balance condition. be employed structures thermodynamic predictions, and diverse generated machine-learning applications.
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ژورنال
عنوان ژورنال: Materials and Manufacturing Processes
سال: 2023
ISSN: ['1042-6914', '1532-2475']
DOI: https://doi.org/10.1080/10426914.2023.2217909