空格(标点符号)
加速度
格子(音乐)
物理
计算机科学
算法
经典力学
声学
操作系统
作者
Bin Xi,Kin Fai Tse,Tsz-Fung Kok,Ho Ming Chan,Man Kit Chan,Ho‐Yin Chan,Kwan Yue Clinton Wong,Robin S. H. Yuen,Junyi Zhu
标识
DOI:10.1021/acs.jpcc.2c03156
摘要
Efficiency of search of wanted materials with desired properties is limited by the huge search space. By deep learning methods, we demonstrate that space group information can be acquired from band structure inputs to reduce the search space. Despite atomic orbital or accidental degeneracies mixed with lattice degeneracies, band degeneracies as input can yield 96.0% prediction accuracy for cubic systems that leads to a 25.1-fold acceleration of searching speed overall. Additionally, for all space groups, the prediction accuracy is 82.0% with overall 36.9-fold acceleration in the search speed. In addition, valence band degeneracies as inputs can yield satisfactory results and may assist in structural analysis from ARPES results.
科研通智能强力驱动
Strongly Powered by AbleSci AI