Bond sensitive graph neural networks for predicting high temperature superconductors

Abstract Finding high temperature superconductors (HTS) has been a continuing challenge due to the difficulty in predicting the transition temperature (Tc) of superconductors. Recently, the efficiency of predicting Tc has been greatly improved via machine learning (ML). Unfortunately, prevailing ML...

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Главные авторы:	Liang Gu, Yang Liu, Pin Chen, Haiyou Huang, Ning Chen, Yang Li, Turab Lookman, Yutong Lu, Yanjing Su
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Wiley-VCH 2024-06-01
Серии:	Materials Genome Engineering Advances
Предметы:	graph neural network machine learning superconductivity superconductors transition temperature
Online-ссылка:	https://doi.org/10.1002/mgea.48
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