Suppr超能文献

随机多组分合金的高效从头算建模

Efficient Ab initio Modeling of Random Multicomponent Alloys.

作者信息

Jiang Chao, Uberuaga Blas P

机构信息

Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA.

出版信息

Phys Rev Lett. 2016 Mar 11;116(10):105501. doi: 10.1103/PhysRevLett.116.105501. Epub 2016 Mar 8.

Abstract

We present in this Letter a novel small set of ordered structures (SSOS) method that allows extremely efficient ab initio modeling of random multicomponent alloys. Using inverse II-III spinel oxides and equiatomic quinary bcc (so-called high entropy) alloys as examples, we demonstrate that a SSOS can achieve the same accuracy as a large supercell or a well-converged cluster expansion, but with significantly reduced computational cost. In particular, because of this efficiency, a large number of quinary alloy compositions can be quickly screened, leading to the identification of several new possible high-entropy alloy chemistries. The SSOS method developed here can be broadly useful for the rapid computational design of multicomponent materials, especially those with a large number of alloying elements, a challenging problem for other approaches.

摘要

在本信函中,我们提出了一种新颖的小有序结构集(SSOS)方法,该方法能够对随机多组分合金进行极其高效的从头算建模。以反II-III尖晶石氧化物和等原子五元体心立方(所谓的高熵)合金为例,我们证明了一个小有序结构集能够达到与大超胞或收敛良好的团簇展开相同的精度,但计算成本显著降低。特别是,由于这种高效性,可以快速筛选大量的五元合金成分,从而确定几种新的可能的高熵合金化学组成。这里开发的小有序结构集方法对于多组分材料的快速计算设计具有广泛的用途,尤其是对于那些含有大量合金元素的材料,这对其他方法来说是一个具有挑战性的问题。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验