Revealing nanostructures in high-entropy alloys via machine-learning accelerated scalable Monte Carlo simulation

Revealing nanostructures in high-entropy alloys via machine-learning accelerated scalable Monte Carlo simulation

Abstract First-principles Monte Carlo (MC) simulations at finite temperatures are computationally prohibitive for large systems due to the high cost of quantum calculations and poor parallelizability of sequential Markov chains in MC algorithms. We introduce scalable Monte Carlo at eXtreme (SMC-X),...

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Bibliographic Details
Main Authors: Xianglin Liu, Kai Yang, Yongxiang Liu, Fanli Zhou, Dengdong Fan, Zongrui Pei, Pengxiang Xu, Yonghong Tian
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:npj Computational Materials
Online Access:https://doi.org/10.1038/s41524-025-01762-8
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https://doi.org/10.1038/s41524-025-01762-8

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