Although high-entropy materials are attracting considerable interest due to a combination of useful properties and promising applications,predicting their formation remains a hindrance for rational discovery of new sy...Although high-entropy materials are attracting considerable interest due to a combination of useful properties and promising applications,predicting their formation remains a hindrance for rational discovery of new systems.Experimental approaches are based on physical intuition and/or expensive trial and error strategies.Most computational methods rely on the availability of sufficient experimental data and computational power.Machine learning(ML)applied to materials science can accelerate development and reduce costs.In this study,we propose an ML method,leveraging thermodynamic and compositional attributes of a given material for predicting the synthesizability(i.e.,entropy-forming ability)of disordered metal carbides.展开更多
The computational prediction of superhard materials would enable the in silico design of compounds that could be used in a wide variety of technological applications.Herein,good agreement was found between experimenta...The computational prediction of superhard materials would enable the in silico design of compounds that could be used in a wide variety of technological applications.Herein,good agreement was found between experimental Vickers hardnesses,Hv,of a wide range of materials and those calculated by three macroscopic hardness models that employ the shear and/or bulk moduli obtained from:(i)first principles via AFLOW-AEL(AFLOW Automatic Elastic Library),and(ii)a machine learning(ML)model trained on materials within the AFLOW repository.Because H^(ML)_(v) values can be quickly estimated,they can be used in conjunction with an evolutionary search to predict stable,superhard materials.This methodology is implemented in the XTALOPT evolutionary algorithm.Each crystal is minimized to the nearest local minimum,and its Vickers hardness is computed via a linear relationship with the shear modulus discovered by Teter.Both the energy/enthalpy and H^(ML)_(v),Teter are employed to determine a structure’s fitness.This implementation is applied towards the carbon system,and 43 new superhard phases are found.A topological analysis reveals that phases estimated to be slightly harder than diamond contain a substantial fraction of diamond and/or lonsdaleite.展开更多
The accelerated growth rate of repository entries in crystallographic databases makes it arduous to identify and classify their prototype structures.The open-source AFLOW-XtalFinder package was developed to solve this...The accelerated growth rate of repository entries in crystallographic databases makes it arduous to identify and classify their prototype structures.The open-source AFLOW-XtalFinder package was developed to solve this problem.It symbolically maps structures into standard designations following the AFLOW Prototype Encyclopedia and calculates the internal degrees of freedom consistent with the International Tables for Crystallography.To ensure uniqueness,structures are analyzed and compared via symmetry,local atomic geometries,and crystal mapping techniques,simultaneously grouping them by similarity.The software(i)distinguishes distinct crystal prototypes and atom decorations,(ii)determines equivalent spin configurations,(iii)reveals compounds with similar properties,and(iv)guides the discovery of unexplored materials.The operations are accessible through a Python module ready for workflows,and through command line syntax.All the 4+million compounds in the AFLOW.org repositories are mapped to their ideal prototype,allowing users to search database entries via symbolic structure-type.Furthermore,15,000 unique structures—sorted by prevalence—are extracted from the AFLOW-ICSD catalog to serve as future prototypes in the Encyclopedia.展开更多
One of the most accurate approaches for calculating lattice thermal conductivity,κ_(l),is solving the Boltzmann transport equation starting from third-order anharmonic force constants.In addition to the underlying ap...One of the most accurate approaches for calculating lattice thermal conductivity,κ_(l),is solving the Boltzmann transport equation starting from third-order anharmonic force constants.In addition to the underlying approximations of ab-initio parameterization,two main challenges are associated with this path:high computational costs and lack of automation in the frameworks using this methodology,which affect the discovery rate of novel materials with ad-hoc properties.Here,the Automatic Anharmonic Phonon Library(AAPL)is presented.It efficiently computes interatomic force constants by making effective use of crystal symmetry analysis,it solves the Boltzmann transport equation to obtain κ_(l),and allows a fully integrated operation with minimum user intervention,a rational addition to the current high-throughput accelerated materials development framework AFLOW.An“experiment vs.theory”study of the approach is shown,comparing accuracy and speed with respect to other available packages,and for materials characterized by strong electron localization and correlation.Combining AAPL with the pseudo-hybrid functional ACBN0 is possible to improve accuracy without increasing computational requirements.展开更多
The need for improved functionalities is driving the search for more complicated multi-component materials.Despite the factorially increasing composition space,ordered compounds with four or more species are rare.Here...The need for improved functionalities is driving the search for more complicated multi-component materials.Despite the factorially increasing composition space,ordered compounds with four or more species are rare.Here,we unveil the competition between the gain in enthalpy and entropy with increasing number of species by statistical analysis of the AFLOW data repositories.A threshold in the number of species is found where entropy gain exceeds enthalpy gain.Beyond that,enthalpy can be neglected,and disorder—complete or partial—is unavoidable.展开更多
The correct calculation of formation enthalpy is one of the enablers of ab-initio computational materials design.For several classes of systems(e.g.oxides)standard density functional theory produces incorrect values.H...The correct calculation of formation enthalpy is one of the enablers of ab-initio computational materials design.For several classes of systems(e.g.oxides)standard density functional theory produces incorrect values.Here we propose the“coordination corrected enthalpies”method(CCE),based on the number of nearest neighbor cation–anion bonds,and also capable of correcting relative stability of polymorphs.CCE uses calculations employing the Perdew,Burke and Ernzerhof(PBE),local density approximation(LDA)and strongly constrained and appropriately normed(SCAN)exchange correlation functionals,in conjunction with a quasiharmonic Debye model to treat zero-point vibrational and thermal effects.The benchmark,performed on binary and ternary oxides(halides),shows very accurate room temperature results for all functionals,with the smallest mean absolute error of 27(24)meV/atom obtained with SCAN.The zero-point vibrational and thermal contributions to the formation enthalpies are small and with different signs—largely canceling each other.展开更多
基金We acknowledge support through the Office of Naval Research ONR-MURI(grant number N00014-15-1-2863)K.K.acknowledges support by the Department of Defense(DoD)through the National Defense Science and Engineering Graduate Fellowship(NDSEG)Program+1 种基金K.K.also acknowledges the financial support of the ARCS Foundation,San Diego ChapterK.S.V.acknowledges the financial generosity of the Oerlikon Group in support of his research group.
文摘Although high-entropy materials are attracting considerable interest due to a combination of useful properties and promising applications,predicting their formation remains a hindrance for rational discovery of new systems.Experimental approaches are based on physical intuition and/or expensive trial and error strategies.Most computational methods rely on the availability of sufficient experimental data and computational power.Machine learning(ML)applied to materials science can accelerate development and reduce costs.In this study,we propose an ML method,leveraging thermodynamic and compositional attributes of a given material for predicting the synthesizability(i.e.,entropy-forming ability)of disordered metal carbides.
基金We acknowledge the DOD-ONR(N00014-16-1-2583 and N00014-17-1-2090)for financial support,and the Center for Computational Research(CCR)at SUNY Buffalo for computational supportD.M.P.thanks the Universitádegi Studi di Milano for the transition grants PSR2015-1718 and FFABR2018.
文摘The computational prediction of superhard materials would enable the in silico design of compounds that could be used in a wide variety of technological applications.Herein,good agreement was found between experimental Vickers hardnesses,Hv,of a wide range of materials and those calculated by three macroscopic hardness models that employ the shear and/or bulk moduli obtained from:(i)first principles via AFLOW-AEL(AFLOW Automatic Elastic Library),and(ii)a machine learning(ML)model trained on materials within the AFLOW repository.Because H^(ML)_(v) values can be quickly estimated,they can be used in conjunction with an evolutionary search to predict stable,superhard materials.This methodology is implemented in the XTALOPT evolutionary algorithm.Each crystal is minimized to the nearest local minimum,and its Vickers hardness is computed via a linear relationship with the shear modulus discovered by Teter.Both the energy/enthalpy and H^(ML)_(v),Teter are employed to determine a structure’s fitness.This implementation is applied towards the carbon system,and 43 new superhard phases are found.A topological analysis reveals that phases estimated to be slightly harder than diamond contain a substantial fraction of diamond and/or lonsdaleite.
基金D.CF acknowkedga support from the Duke University Provosts Potdactonal Rellowship Program SC xknowi edas suppart by DOD-ONR(ND001417-1-2090)the Alaxandar von Humbaidh Foundation。
文摘The accelerated growth rate of repository entries in crystallographic databases makes it arduous to identify and classify their prototype structures.The open-source AFLOW-XtalFinder package was developed to solve this problem.It symbolically maps structures into standard designations following the AFLOW Prototype Encyclopedia and calculates the internal degrees of freedom consistent with the International Tables for Crystallography.To ensure uniqueness,structures are analyzed and compared via symmetry,local atomic geometries,and crystal mapping techniques,simultaneously grouping them by similarity.The software(i)distinguishes distinct crystal prototypes and atom decorations,(ii)determines equivalent spin configurations,(iii)reveals compounds with similar properties,and(iv)guides the discovery of unexplored materials.The operations are accessible through a Python module ready for workflows,and through command line syntax.All the 4+million compounds in the AFLOW.org repositories are mapped to their ideal prototype,allowing users to search database entries via symbolic structure-type.Furthermore,15,000 unique structures—sorted by prevalence—are extracted from the AFLOW-ICSD catalog to serve as future prototypes in the Encyclopedia.
基金support by the DOE(DE-AC02-05CH11231),specifically the Basic Energy Sciences program under Grant#EDCBEEpartial support by DOD-ONR(N00014-13-1-0635,N00014-11-1-0136,and N00014-15-1-2863)the Alexander von Humboldt Foundation for financial support(Fritz-Haber-Institut der Max-Planck-Gesellschaft,14195 Berlin-Dahlem,Germany).
文摘One of the most accurate approaches for calculating lattice thermal conductivity,κ_(l),is solving the Boltzmann transport equation starting from third-order anharmonic force constants.In addition to the underlying approximations of ab-initio parameterization,two main challenges are associated with this path:high computational costs and lack of automation in the frameworks using this methodology,which affect the discovery rate of novel materials with ad-hoc properties.Here,the Automatic Anharmonic Phonon Library(AAPL)is presented.It efficiently computes interatomic force constants by making effective use of crystal symmetry analysis,it solves the Boltzmann transport equation to obtain κ_(l),and allows a fully integrated operation with minimum user intervention,a rational addition to the current high-throughput accelerated materials development framework AFLOW.An“experiment vs.theory”study of the approach is shown,comparing accuracy and speed with respect to other available packages,and for materials characterized by strong electron localization and correlation.Combining AAPL with the pseudo-hybrid functional ACBN0 is possible to improve accuracy without increasing computational requirements.
基金Research sponsored by DODONR(N00014-15-1-2863,N00014-16-1-2326,and N00014-17-1-2876).
文摘The need for improved functionalities is driving the search for more complicated multi-component materials.Despite the factorially increasing composition space,ordered compounds with four or more species are rare.Here,we unveil the competition between the gain in enthalpy and entropy with increasing number of species by statistical analysis of the AFLOW data repositories.A threshold in the number of species is found where entropy gain exceeds enthalpy gain.Beyond that,enthalpy can be neglected,and disorder—complete or partial—is unavoidable.
基金Research supported by DOD-ONR(N00014-15-1-2863,N00014-15-1-2266,N00014-17-1-2090,N00014-16-1-2326,N00014-17-1-2876)R.F.acknowledges support from the Alexander von Humboldt foundation under the Feodor Lynen research fellowship+1 种基金C.O.acknowledges support from the National Science Foundation Graduate Research Fellowship under Grant no.DGF-1106401S.C.acknowledges financial support from the Alexander von Humboldt foundation.
文摘The correct calculation of formation enthalpy is one of the enablers of ab-initio computational materials design.For several classes of systems(e.g.oxides)standard density functional theory produces incorrect values.Here we propose the“coordination corrected enthalpies”method(CCE),based on the number of nearest neighbor cation–anion bonds,and also capable of correcting relative stability of polymorphs.CCE uses calculations employing the Perdew,Burke and Ernzerhof(PBE),local density approximation(LDA)and strongly constrained and appropriately normed(SCAN)exchange correlation functionals,in conjunction with a quasiharmonic Debye model to treat zero-point vibrational and thermal effects.The benchmark,performed on binary and ternary oxides(halides),shows very accurate room temperature results for all functionals,with the smallest mean absolute error of 27(24)meV/atom obtained with SCAN.The zero-point vibrational and thermal contributions to the formation enthalpies are small and with different signs—largely canceling each other.
