Influence of chemistry and structure on interfacial segregation in NbMoTaW with high-throughput atomistic simulations
Influence of chemistry and structure on interfacial segregation in NbMoTaW with high-throughput atomistic simulations
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DOI：
10.1063/5.0130402
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发表时间：
2022-10
影响因子：
3.2
通讯作者：
Ian Geiger;Jian Luo;E. Lavernia;P. Cao;D. Apelian;T. Rupert
中科院分区：
文献类型：
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作者：
Ian Geiger;Jian Luo;E. Lavernia;P. Cao;D. Apelian;T. Rupert
难熔多主元素合金具有良好的高温强度保持性等优良的力学性能，已引起人们的广泛关注。虽然其固有的化学复杂性被认为是一个定义的功能，在预测局部化学排序，特别是在晶界区域的增强结构紊乱的挑战。在这项研究中，我们使用原子模拟的一大群双晶体模型的样品各种各样的界面的网站（晶界）在NbMoTaW和探索紧急趋势的界面偏析和潜在的结构和化学驱动因素。采样数百双晶体沿着[001]对称倾斜轴和分析超过十三万晶界网站与各种当地的原子环境，我们发现在NbMoTaW偏析的趋势。虽然Nb是占主导地位的偏析，更值得注意的是偏析模式，偏离预期的行为和标记的情况下，当地的结构和化学驱动力导致有趣的偏析事件。例如，不完全耗尽的Ta在低角度的边界结果从化学钉扎由于有利的局部组成环境与化学短程有序。最后，开发了捕获和比较界面位点的结构和化学特征的机器学习模型，以权衡它们的相对重要性和对分离趋势的贡献，揭示了在包括局部化学信息时预测能力的显着增加。总体而言，这项工作，突出了复杂的局部晶界结构和化学短程有序之间的相互作用，建议可调偏析和化学有序的定制多主元素合金的晶界结构。
Refractory multi-principal element alloys exhibiting promising mechanical properties such as excellent strength retention at elevated temperatures have been attracting increasing attention. Although their inherent chemical complexity is considered a defining feature, a challenge arises in predicting local chemical ordering, particularly in grain boundary regions with an enhanced structural disorder. In this study, we use atomistic simulations of a large group of bicrystal models to sample a wide variety of interfacial sites (grain boundary) in NbMoTaW and explore emergent trends in interfacial segregation and the underlying structural and chemical driving factors. Sampling hundreds of bicrystals along the [001] symmetric tilt axis and analyzing more than one hundred and thirty thousand grain boundary sites with a variety of local atomic environments, we uncover segregation trends in NbMoTaW. While Nb is the dominant segregant, more notable are the segregation patterns that deviate from expected behavior and mark situations where local structural and chemical driving forces lead to interesting segregation events. For example, incomplete depletion of Ta in low-angle boundaries results from chemical pinning due to favorable local compositional environments associated with chemical short-range ordering. Finally, machine learning models capturing and comparing the structural and chemical features of interfacial sites are developed to weigh their relative importance and contributions to segregation tendency, revealing a significant increase in predictive capability when including local chemical information. Overall, this work, highlighting the complex interplay between the local grain boundary structure and chemical short-range ordering, suggests tunable segregation and chemical ordering by tailoring grain boundary structure in multi-principal element alloys.