journal article·2023-01

Hydrogen trapping, desorption and clustering in heterophase interfaces of W-ZrC alloy

Yange Zhang, Xiangyan Li, Yichun Xu, Yawei Lei, Zhuoming Xie, Xianping Wang, Qianfeng Fang, Changsong Liu, Xuebang Wu

Acta Materialia· Volume 242
Publisher page

Abstract

Understanding the interaction of hydrogen (H) with defects has been recognized as a central aspect in hydrogen-induced damages in metals. In this work, the role of coherent and semi-coherent interfaces between W and ZrC on H trapping, desorption and clustering in nanostructured W alloys was investigated by density functional theory calculations. It is found that, the trapping ability of pure interface is comparable with the intrinsic defects (grain boundary, dislocations) in bulk W, with segregation energies of H ranging from -1.37 to -0.98 eV. While the interfaces with W/C vacancy show stronger trapping capabilities, especially for the semi-coherent interfaces. This leads to low peak temperatures of 390–567 K for H desorption from the pure interfaces and high peak temperatures of 470–836 K from the vacancy-containing interfaces. As the number of H atoms increases, they preferentially segregate to the interfacial W vacancy and divacancy, and then stay at the interface and interface-like zones discretely until the adsorption rate reaches 3/8. The strong traps of vacancy-containing phase interfaces could effectively absorb H from the screw dislocation cores and bulk vacancies in W, hence preventing H-induced damage. This work advances atomic-level understanding of the role of phase interfaces in H trapping and clustering, not only offering direct explanations for experimental H desorption observations, but also pointing to a feasible route towards interface engineering against H-induced damage in structural metals.
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Research context

OpenAlex topics: Fusion materials and technologies · Nuclear Materials and Properties · Hydrogen embrittlement and corrosion behaviors in metals

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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