Chemical short-range order in complex concentrated alloys
Chemical short-range order in complex concentrated alloys
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DOI：
10.1557/s43577-023-00575-8
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发表时间：
2023-07
期刊：
影响因子：
5
通讯作者：
Wei Chen;Lin Li;Qiang Zhu;Houlong Zhuang
中科院分区：
文献类型：
--
作者：
Wei Chen;Lin Li;Qiang Zhu;Houlong Zhuang
复杂的浓缩合金(CCA)引起了材料研究界和其他领域的极大关注。由于CCA在组成和结构上的巨大自由度可以产生具有广泛应用的新型性质(如结构和功能)，因此CCA的结构-性质关系是人们非常感兴趣的。CCA原子结构的一个显著特征是存在化学短程有序(CSRO)。了解CSRO在性质上的作用，特别是相稳定性，需要实验和计算方法的共同努力。在这篇文章中，我们首先简要回顾了最近在识别和表征不同CCA的CSRO方面的最新实验努力。然后，我们将重点介绍已用于研究CSRO效应的理论和计算技术。这些计算方法包括密度泛函理论(DFT)、分子动力学(MD)和统计力学方法(如团簇展开)和机器学习方法(如创建可转移的原子间势)。最后，我们概述了CSRO研究在CCAs中面临的挑战和未来的方向。
Complex concentrated alloys (CCAs) have drawn immense attention from the materials research community and beyond. Because the vast compositional and structural degrees of freedom in CCAs can lead to novel properties (e.g., structural and functional) with a wide range of applications, the structure–property relationships of CCAs are of critical interest. One salient feature in the atomic structures of CCAs is the presence of chemical short-range ordering (CSRO). Understanding the roles of CSRO on properties, especially phase stability, requires joint efforts from experimental and computational approaches. In this article, we first briefly survey the most recent experimental efforts in identifying and characterizing CSRO of various CCAs. We then focus on the theoretical and computational techniques that have been deployed to investigate the CSRO effects. These computational methods include density functional theory (DFT), molecular dynamics (MD), and statistical mechanics methods such as cluster expansions and machine learning methods such as creating transferable interatomic potentials. Finally, we outline the challenges and future directions of CSRO research in CCAs.