InvDesFlow: An AI-Driven Materials Inverse Design Workflow to Explore Possible High-Temperature Superconductors  

作　　者：Xiao-Qi Han Zhenfeng Ouyang Peng-Jie Guo Hao Sun Ze-Feng Gao Zhong-Yi Lu 韩小琪;欧阳振峰;郭朋杰;孙浩;高泽峰;卢仲毅

机构地区：[1]School of Physics and Beijing Key Laboratory of Opto-electronic Functional Materials&Micro-nano Devices,Renmin University of China,Beijing 100872,China [2]Key Laboratory of Quantum State Construction and Manipulation(Ministry of Education),Renmin University of China,Beijing100872,China [3]Hefei National Laboratory,Hefei230088,China [4]Gaoling School of Artificial Intelligence,Renmin University of China,Beijing100872,China

出　　处：《Chinese Physics Letters》2025年第4期85-98,共14页中国物理快报(英文版)

基　　金：financially supported by the National Natural Science Foundation of China(Grant Nos.62476278,12434009,and 12204533);the National Key R&D Program of China(Grant No.2024YFA1408601);the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0302402)。

摘　　要：The discovery of new superconducting materials,particularly those exhibiting high critical temperature(Tc),has been a vibrant area of study within the field of condensed matter physics.Conventional approaches primarily rely on physical intuition to search for potential superconductors within the existing databases.However,the known materials only scratch the surface of the extensive array of possibilities within the realm of materials.

关 键 词：physical intuition superconducting materialsparticularly condensed matter physicsconventional high temperature superconductors AI driven materials exploration inverse design 

分 类 号：O469[理学—凝聚态物理]