Chemical short-range order regulates hydrogen energetics and hydrogen-dislocation interactions in CoNiV

IF 13.1 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Beihan Chen, Dalia M. Sayed Ahmed, Yang Yang, Miaomiao Jin
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引用次数: 0

Abstract

Chemical short-range order (CSRO) has emerged as a critical structural feature in concentrated alloys, yet its coupling with hydrogen remains an active discussion. Here, we develop a machine-learning interatomic potential for the Co-Ni-V-H system and investigate how CSRO regulates hydrogen energetics and dislocation behavior in CoNiV, an alloy with reported strong resistance to hydrogen embrittlement. We identify strong V-centered ordering that suppresses V–V clustering and remains robust up to 1000 K, with negligible changes upon the addition of 1.0 at.% hydrogen. Compared to a chemically random alloy, the ordered state exhibits higher average hydrogen solution energies and a reduced population of strongly binding sites, suggesting lower bulk hydrogen uptake. At partial dislocations, hydrogen preferentially segregates to tensile core regions, where the dislocation core acts as a shallow, reversible trap, with a much weaker effect compared to chemical trapping states. These results show that robust local chemical order plays a critical role in affecting H uptake, partitioning, and dislocation trapping in concentrated CoNiV alloys.
化学短程顺序调节CoNiV中氢能量和氢位错相互作用
化学短程有序(CSRO)已成为浓合金的一个重要结构特征,但它与氢的耦合仍然是一个活跃的讨论。在这里,我们开发了Co-Ni-V-H体系的机器学习原子间势,并研究了CSRO如何调节CoNiV(一种具有较强抗氢脆性的合金)中的氢能量学和位错行为。我们发现了强大的以v为中心的排序,它抑制V-V聚类,并且在1000 K以内保持鲁棒性,在添加1.0 at时变化可以忽略不计。%氢。与化学无序合金相比,有序态表现出更高的平均氢溶解能和更少的强结合位点,表明更低的总体氢吸收。在部分位错中,氢优先分离到拉伸核区域,在那里位错核作为一个浅的、可逆的陷阱,与化学陷阱状态相比,效果要弱得多。这些结果表明,在高浓度CoNiV合金中,强大的局部化学顺序对H的吸收、分配和位错捕获起着关键作用。
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来源期刊
npj Computational Materials
npj Computational Materials Mathematics-Modeling and Simulation
CiteScore
15.30
自引率
5.20%
发文量
229
审稿时长
6 weeks
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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