Two-dimensional(2D)materials attract considerable attention due to their remarkable electronic,mechanical and optical properties.Despite their use in combination with substrates in practical applications,computational...Two-dimensional(2D)materials attract considerable attention due to their remarkable electronic,mechanical and optical properties.Despite their use in combination with substrates in practical applications,computational studies often neglect the effects of substrate interactions for simplicity.This study presents a novel method for predicting the atomic structure of 2D materials on substrates by combining an evolutionary algorithm,a lattice-matching technique,an automated machinelearning interatomic potentials training protocol,and the ab initio thermodynamics approach.Using the molybdenum-sulfur system on a sapphire substrate as a case study,we reveal several new stable and metastable structures,including previously known 1H-MoS_(2)and newly found Pmma Mo_(3)S_(2),P1^(-)Mo_(2)S,P2_(1)m Mo_(5)S_(3),and P_(4)mm Mo_(4)S,where the Mo_(4)S structure is specifically stabilized by interaction with the substrate.Finally,we use the ab initio thermodynamics approach to predict the synthesis conditions of the discovered structures in the parameter space of the commonly used chemical vapor deposition technique.展开更多
基金RSF No.24-73-10055 for financial support of the development of ML interatomic potential for Mo-S system and calculation of dynamical properties of newly found materialsA.V.A.is supported by the Ministry of Science and Higher Education(FSMG-2025-0005)+3 种基金D.G.K.acknowledges financial support from the federal budget of the Russian Ministry of Science and Higher Education(No.125020401357-4)A.R.O.gratefully acknowledges support from Russian Science Foundation(grant 24-43-00162)K.S.N acknowledges support from the Ministry of Education,Singapore under Research Centre of Excellence award to the Institute for Functional Intelligent Materials,I-FIM(project No.EDUNC-33-18-279-V12)and under the Tier 3 program(MOE-MOET32024-0001)the National Research Foundation,Singapore under its AI Singapore Programme(AISG Award No:AISG3-RP-2022-028).
文摘Two-dimensional(2D)materials attract considerable attention due to their remarkable electronic,mechanical and optical properties.Despite their use in combination with substrates in practical applications,computational studies often neglect the effects of substrate interactions for simplicity.This study presents a novel method for predicting the atomic structure of 2D materials on substrates by combining an evolutionary algorithm,a lattice-matching technique,an automated machinelearning interatomic potentials training protocol,and the ab initio thermodynamics approach.Using the molybdenum-sulfur system on a sapphire substrate as a case study,we reveal several new stable and metastable structures,including previously known 1H-MoS_(2)and newly found Pmma Mo_(3)S_(2),P1^(-)Mo_(2)S,P2_(1)m Mo_(5)S_(3),and P_(4)mm Mo_(4)S,where the Mo_(4)S structure is specifically stabilized by interaction with the substrate.Finally,we use the ab initio thermodynamics approach to predict the synthesis conditions of the discovered structures in the parameter space of the commonly used chemical vapor deposition technique.
