标题： 利用机器学习势研究MoNbTaVW高熵合金的增强辐射耐受性 显示英文标题

标题： Utilizing a machine-learned potential to explore enhanced radiation tolerance in the MoNbTaVW high-entropy alloy

摘要： 高熵合金（HEAs）以钨（W）为基础，由于其优异的辐照抗性，已成为未来聚变反应堆等离子体面对组件的有希望的候选材料。 在本研究中，我们构建了用于MoNbTaVW五元体系的有效机器学习原子间势。 该势能计算速度与嵌入原子方法（EAM）势相当，使我们能够通过分子动力学模拟对初级辐射损伤进行综合研究。 研究并比较了MoNbTaVW HEA中的阈值位移能（TDE）与纯金属。 一系列初级碰撞原子能量范围从10到150 keV的位移级联模拟显示，MoNbTaVW HEA和纯W在缺陷生成和聚集方面存在显著差异。在HEAs中，我们观察到更多的存活弗伦克尔对（FPs），但间隙团簇更少且更小，表明具有更好的辐照耐受性。 我们提出了扩展的损伤模型来量化MoNbTaVW HEA中的辐照剂量，并建议其增强的抗性原因之一是次级级联分裂，这减少了间隙团簇的形成。 我们的研究结果为难熔体心立方合金的基本辐照抗性机制提供了关键见解，为未来抗辐照材料的设计提供了指导。 显示英文摘要

摘要： High-entropy alloys (HEAs) based on tungsten (W) have emerged as promising candidates for plasma-facing components in future fusion reactors, owing to their excellent irradiation resistance. In this study, we construct an efficient machine-learned interatomic potential for the MoNbTaVW quinary system. This potential achieves computational speeds comparable to the embedded-atom method (EAM) potential, allowing us to conduct a comprehensive investigation of the primary radiation damage through molecular dynamics simulations. Threshold displacement energies (TDEs) in the MoNbTaVW HEA are investigated and compared with pure metals. A series of displacement cascade simulations at primary knock-on atom energies ranging from 10 to 150 keV reveal significant differences in defect generation and clustering between MoNbTaVW HEA and pure W. In HEAs, we observe more surviving Frenkel pairs (FPs) but fewer and smaller interstitial clusters compared to W, indicating superior radiation tolerance. We propose extended damage models to quantify the radiation dose in the MoNbTaVW HEA, and suggest that one reason for their enhanced resistance is subcascade splitting, which reduces the formation of interstitial clusters. Our findings provide critical insights into the fundamental irradiation resistance mechanisms in refractory body-centered cubic alloys, offering guidance for the design of future radiation-tolerant materials.