Chemically disordered materials are widely utilized,yet establishing structure-property relationship remains challenging due to their vast configurational space.Identifying thermal accessible low energy configurations...Chemically disordered materials are widely utilized,yet establishing structure-property relationship remains challenging due to their vast configurational space.Identifying thermal accessible low energy configurations of these materials through standard ab initio calculations is computationally expensive for doping induced structure changes.In this work,we propose a straightforward algorithm to optimize random structures into ground state configurations by matching chemical subgraphs.This algorithm constructs harmonic potential with chemistry-driven parameterization,without relying on iterative training to accelerate the relaxation process.It can completely bypass the need for relaxation with ab initio calculations in rigid systems and reduce computational costs by 30%in flexible systems.Leveraging its exceptional structural relaxation capabilities,we have also developed a generalized workflow for screening low-energy structures in disordered materials,aimed at expediting the screening process and accelerating new material discovery.展开更多
基金supported by the National Science Fund for Distinguished Young Scholars of China(Grant No.22225206)the National Key R&D Program of China(No.2022YFA1604103)+5 种基金the National Natural Science Foundation of China(Nos.22202224,21972157)the CAS Project for Young Scientists in Basic Research(YSBR-005)the Key Research Program of Frontier Sciences CAS(ZDBS-LY-7007)the Major Research Plan of the National Natural Science Foundation of China(92045303)the Informatization Plan of the Chinese Academy of Sciences(Grant No.CAS-WX2021SF0110)Funding support was also received from the Beijing Advanced Innovation Center for Materials Genome Engineering,Synfuels China Co.,Ltd.,and the Institute of Coal Chemistry,Chinese Academy of Sciences.
文摘Chemically disordered materials are widely utilized,yet establishing structure-property relationship remains challenging due to their vast configurational space.Identifying thermal accessible low energy configurations of these materials through standard ab initio calculations is computationally expensive for doping induced structure changes.In this work,we propose a straightforward algorithm to optimize random structures into ground state configurations by matching chemical subgraphs.This algorithm constructs harmonic potential with chemistry-driven parameterization,without relying on iterative training to accelerate the relaxation process.It can completely bypass the need for relaxation with ab initio calculations in rigid systems and reduce computational costs by 30%in flexible systems.Leveraging its exceptional structural relaxation capabilities,we have also developed a generalized workflow for screening low-energy structures in disordered materials,aimed at expediting the screening process and accelerating new material discovery.
