The discovery of high-dielectric materials is crucial to increasing the efficiency of electronic devices and batteries.Here,we report three previously unexplored materials with very high dielectric constants(69<ϵ&l...The discovery of high-dielectric materials is crucial to increasing the efficiency of electronic devices and batteries.Here,we report three previously unexplored materials with very high dielectric constants(69<ϵ<101)and large band gaps(2.9<E_(g)(eV)<5.5)obtained by screening materials databases using statistical optimization algorithms aided by artificial neural networks(ANN).Two of these new dielectrics are mixed-anion compounds(Eu_(5)SiCl_(6)O_(4)and HoClO)and are shown to be thermodynamically stable against common semiconductors via phase diagram analysis.We also uncovered four other materials with relatively large dielectric constants(20<ϵ<40)and band gaps(2.3<E_(g)(eV)<2.7).While the ANN training-data are obtained from the Materials Project,the search-space consists of materials from the Open Quantum Materials Database(OQMD)—demonstrating a successful implementation of cross-database materials design.Overall,we report the dielectric properties of 17 materials calculated using ab initio calculations,that were selected in our design workflow.The dielectric materials with high-dielectric properties predicted in this work open up further experimental research opportunities.展开更多
基金This work was funded by the SAMSUNG Global Research Outreach Program,and the U.S.Department of Commerce,National Institute of Standards and Technology as part of the Center for Hierarchical Materials Design(CHiMaD)award 70NANB14H012We acknowledge the computing resources provided by the National Energy Research Scientific Computing Center(NERSC),a U.S.Department of Energy Office of Science User Facility operated under Contract No.DE-AC02-05CH11231+1 种基金Quest high-performance computing facility at Northwestern University which is jointly supported by the Office of the Provost,the Office for Research,and Northwestern University Information Technologythe Extreme Science and Engineering Discovery Environment(National Science Foundation Contract ACI-1548562).
文摘The discovery of high-dielectric materials is crucial to increasing the efficiency of electronic devices and batteries.Here,we report three previously unexplored materials with very high dielectric constants(69<ϵ<101)and large band gaps(2.9<E_(g)(eV)<5.5)obtained by screening materials databases using statistical optimization algorithms aided by artificial neural networks(ANN).Two of these new dielectrics are mixed-anion compounds(Eu_(5)SiCl_(6)O_(4)and HoClO)and are shown to be thermodynamically stable against common semiconductors via phase diagram analysis.We also uncovered four other materials with relatively large dielectric constants(20<ϵ<40)and band gaps(2.3<E_(g)(eV)<2.7).While the ANN training-data are obtained from the Materials Project,the search-space consists of materials from the Open Quantum Materials Database(OQMD)—demonstrating a successful implementation of cross-database materials design.Overall,we report the dielectric properties of 17 materials calculated using ab initio calculations,that were selected in our design workflow.The dielectric materials with high-dielectric properties predicted in this work open up further experimental research opportunities.
