Sheuly Ghosh, Katharina Ueltzen, Janine George, Jörg Neugebauer, Fritz Körmann
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引用次数: 0
Abstract
The impact of magnetism on chemical ordering in face-centered cubic CrCoNi medium entropy alloy is studied by a combination of ab initio simulations, machine learning potentials, and Monte Carlo simulations. Large magnetic energies are revealed for some mixed L12/L10 type ordered configurations, which are rooted in strong nearest-neighbor magnetic exchange interactions and chemical bonding among the constituent elements. There is a delicate interplay between magnetism and stability of MoPt2 and L12/L10 type of order, which may explain opposing experimental and theoretical findings.
通过结合 ab initio 模拟、机器学习势和蒙特卡罗模拟，研究了磁性对面心立方铬钴镍中熵合金化学有序性的影响。一些 L12/L10 类型的混合有序构型具有较大的磁能，其根源在于组成元素之间的强近邻磁交换相互作用和化学键。MoPt2 的磁性和稳定性与 L12/L10 有序类型之间存在着微妙的相互作用，这也许可以解释实验和理论发现之间的对立。
期刊介绍：
npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings.
Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.
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