材料科学
化学计量学
氢化物
碱金属
超导电性
环境压力
维数之咒
化学物理
无机化学
凝聚态物理
物理化学
冶金
热力学
计算机科学
化学
有机化学
金属
物理
机器学习
作者
Tiago F. T. Cerqueira,Yue‐Wen Fang,Ion Errea,Antonio Sanna,Miguel A. L. Marques
标识
DOI:10.1002/adfm.202404043
摘要
Abstract A machine‐learning‐assisted approach is employed to search for superconducting hydrides under ambient pressure within an extensive dataset comprising over 150 000 compounds. The investigation yields ≈50 systems with transition temperatures surpassing 20 K, and some even reaching above 70 K. These compounds have very different crystal structures, with different dimensionality, chemical composition, stoichiometry, and arrangement of the hydrogens. Interestingly, most of these systems display slight thermodynamic instability, implying that their synthesis will re quire conditions beyond ambient equilibrium. Moreover, a consistent chemical composition is found in the majority of these systems, which combines alkali or alkali‐earth elements with noble metals. This observation suggests a promising avenue for future experimental investigations into high‐temperature superconductivity within hydrides at ambient pressure.
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