SuperBand: an Electronic-band and Fermi surface structure database of superconductors

被引:1
作者
Zhang, Tengdong [1 ]
Suo, Chenyu [1 ]
Wu, Yanling [1 ]
Xu, Xiaodan [1 ]
Liu, Yong [1 ]
Yao, Dao-Xin [2 ]
Li, Jun [1 ]
机构
[1] Yanshan Univ, Sch Sci, State Key Lab Metastable Mat Sci & Technol, Hebei Key Lab Microstruct Mat Phys, Qinhuangdao 066004, Peoples R China
[2] Sun Yat Sen Univ, Sch Phys, State Key Lab Optoelect Mat & Technol, Guangdong Prov Key Lab Magnetoelectr Phys & Device, Guangzhou 510275, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
INTERFACE;
D O I
10.1038/s41597-025-05015-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In comparison to simpler data such as chemical formulas and lattice structures, electronic band structure data provide a more fundamental and intuitive insight into superconducting phenomena. In this work, we generate superconductor's lattice structure files optimized for density functional theory (DFT) calculations. Through DFT, we obtain electronic band for superconductors, including band structures, density of states (DOS), and Fermi surface data. Additionally, we outline efficient methodologies for acquiring structure data, establish high-throughput DFT computational protocols, and introduce tools for extracting this data from large-scale DFT calculations. As an example, we have curated a dataset containing information on 1,362 superconductors along with their experimentally determined superconducting transition temperatures (Tc) as well as 1,112 experimentally verified non-superconducting materials, which is well-suited for machine learning applications. This dataset is constructed with a focus on data quality, accessibility, and usability for machine learning models aimed at predicting superconducting properties.
引用
收藏
页数:9
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