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.
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.
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