Modelling radiation resistant low activation High Entropy Alloys

抗辐射低活化高熵合金建模

• 批准号: EP/S032835/1
• 负责人: Andrew Duff
• 金额: $ 2.81万
• 依托单位: Science and Technology Facilities Council
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FS032835%2F1
• 关键词: Modelling; radiation; resistant; low; activation

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

目前，GtR 中尚未提供所有资助研究的摘要。这通常是因为在提交提案时不需要摘要，但可能是因为它包含个人详细信息等敏感信息。

项目成果

Thermodynamics up to the melting point in a TaVCrW high entropy alloy: Systematic a b i n i t i o study aided by machine learning potentials

TaVCrW 高熵合金熔点的热力学：机器学习潜力辅助的系统化分析研究

• DOI: 10.1103/physrevb.105.214302
• 发表时间: 2022
• 期刊: Physical Review B
• 影响因子: 3.7
• 作者: Zhou Y

Performance of two complementary machine-learned potentials in modelling chemically complex systems

• DOI: 10.1038/s41524-023-01073-w
• 发表时间: 2023-07
• 期刊: npj Computational Materials
• 影响因子: 9.7
• 作者: Konstantin Gubaev;Viktor Zaverkin;P. Srinivasan;A. Duff;Johannes Kästner;B. Grabowski

Exploring the limits of machine-learned potentials for chemically complex multicomponent systems

探索化学复杂多组分系统的机器学习潜力的极限

• DOI: 10.21203/rs.3.rs-2073581/v1
• 发表时间: 2022
• 作者: Gubaev K