Enhancing the ionic conductivity of sulfide solid electrolytes(SEs)through dual-doping is a well-established approach,yet the atomic-level mechanisms driving these improvements remain elusive.By dual-doping Ge and Cl ...Enhancing the ionic conductivity of sulfide solid electrolytes(SEs)through dual-doping is a well-established approach,yet the atomic-level mechanisms driving these improvements remain elusive.By dual-doping Ge and Cl into the Li_(10)GeP_(2)S_(12)(LGPS)framework,we synthesized Ge/Cl-doped LGPS(Li_(10+x)Ge_(1+2x)P_(2−2x)S_(12−x)Cl_(x),x=0.3)with an ionic conductivity of 12.4 mS/cm at 25℃,a value that stands among the highest for LGPS-type SEs.This achievement emphasizes the pivotal role of dopant selection in modulating Li-ion transport mechanisms,thereby enhancing SE performance.Our research elucidates the intricate atomic mechanisms responsible for this enhanced ionic conductivity,with a particular focus on the synergistic effects of Ge and Cl dual-doping.Integrating advanced multianalytical techniques,including experiments and atomistic modeling(machine-learning-assisted molecular dynamics simulations and density functional theory calculations),we provide comprehensive insights into the structure-property relationship in Ge/Cl-doped LGPS SEs.Our findings reveal that Cl doping significantly enhances the paddle-wheel dynamics,while Ge doping promotes cooperative Li diffusion through the formation of Li interstitials.This dual-doping approach not only elucidates the structural and functional dynamics of SEs but also paves the way for designing dopants to enhance ionic conductivity.The insights gained from this study offer a strategic direction for developing higher-performance SEs,highlighting the importance of tailored dopant selection in advancing energy storage technologies.展开更多
Point defects are a universal feature of crystals.Their identification is addressed by combining experimental measurements with theoretical models.The standard modelling approach is,however,prone to missing the ground...Point defects are a universal feature of crystals.Their identification is addressed by combining experimental measurements with theoretical models.The standard modelling approach is,however,prone to missing the ground state atomic configurations associated with energy-lowering reconstructions from the idealised crystallographic environment.Missed ground states compromise the accuracy of calculated properties.To address this issue,we report an approach to navigate the defect configurational landscape using targeted bond distortions and rattling.Application of our workflow to eight materials(CdTe,GaAs,Sb_(2)S_(3),Sb_(2)Se_(3),CeO_(2),In_(2)O_(3),ZnO,anatase-TiO_(2))reveals symmetry breaking in each host crystal that is not found via conventional local minimisation techniques.The point defect distortions are classified by the associated physico-chemical factors.We demonstrate the impact of these defect distortions on derived properties,including formation energies,concentrations and charge transition levels.Our work presents a step forward for quantitative modelling of imperfect solids.展开更多
Calculations of point defect energetics with Density Functional Theory(DFT)can provide valuable insight into several optoelectronic,thermodynamic,and kinetic properties.These calculations commonly use methods ranging ...Calculations of point defect energetics with Density Functional Theory(DFT)can provide valuable insight into several optoelectronic,thermodynamic,and kinetic properties.These calculations commonly use methods ranging from semi-local functionals with a-posteriori corrections to more computationally intensive hybrid functional approaches.For applications of DFT-based high-throughput computation for data-driven materials discovery,point defect properties are of interest,yet are currently excluded from available materials databases.This work presents a benchmark analysis of automated,semi-local point defect calculations with a-posteriori corrections,compared to 245“gold standard”hybrid calculations previously published.We consider three different a-posteriori correction sets implemented in an automated workflow,and evaluate the qualitative and quantitative differences among four different categories of defect information:thermodynamic transition levels,formation energies,Fermi levels,and dopability limits.We highlight qualitative information that can be extracted from high-throughput calculations based on semi-local DFT methods,while also demonstrating the limits of quantitative accuracy.展开更多
基金European Research Council,Grant/Award Number:758345National Research Foundation of Korea,Grant/Award Numbers:NRF-2021R1A2C2009596,RS-2023-00236572,NRF-2022M3J1A1054151Engineering and Physical Sciences Research Council,Grant/Award Numbers:EP/R029431,EP/P020194,EP/T022213。
文摘Enhancing the ionic conductivity of sulfide solid electrolytes(SEs)through dual-doping is a well-established approach,yet the atomic-level mechanisms driving these improvements remain elusive.By dual-doping Ge and Cl into the Li_(10)GeP_(2)S_(12)(LGPS)framework,we synthesized Ge/Cl-doped LGPS(Li_(10+x)Ge_(1+2x)P_(2−2x)S_(12−x)Cl_(x),x=0.3)with an ionic conductivity of 12.4 mS/cm at 25℃,a value that stands among the highest for LGPS-type SEs.This achievement emphasizes the pivotal role of dopant selection in modulating Li-ion transport mechanisms,thereby enhancing SE performance.Our research elucidates the intricate atomic mechanisms responsible for this enhanced ionic conductivity,with a particular focus on the synergistic effects of Ge and Cl dual-doping.Integrating advanced multianalytical techniques,including experiments and atomistic modeling(machine-learning-assisted molecular dynamics simulations and density functional theory calculations),we provide comprehensive insights into the structure-property relationship in Ge/Cl-doped LGPS SEs.Our findings reveal that Cl doping significantly enhances the paddle-wheel dynamics,while Ge doping promotes cooperative Li diffusion through the formation of Li interstitials.This dual-doping approach not only elucidates the structural and functional dynamics of SEs but also paves the way for designing dopants to enhance ionic conductivity.The insights gained from this study offer a strategic direction for developing higher-performance SEs,highlighting the importance of tailored dopant selection in advancing energy storage technologies.
基金I.M.L.thanks La Caixa Foundation for funding a postgraduate scholarship(ID 100010434,fellowship code LCF/BQ/EU20/11810070)S.R.K.acknowledges the EPSRC Centre for Doctoral Training in the Advanced Characterisation of Materials(CDT-ACM)(EP/S023259/1)for funding a PhD studentship+2 种基金DOS acknowledges support from the EPSRC(EP/N01572X/1)and from the European Research Council,ERC(Grant No.758345)Via membership of the UK’s HEC Materials Chemistry Consortium,which is funded by the EPSRC(EP/L000202,EP/R029431,EP/T022213)this work used the UK Materials and Molecular Modelling(MMM)Hub(Thomas EP/P020194 and Young EP/T022213).
文摘Point defects are a universal feature of crystals.Their identification is addressed by combining experimental measurements with theoretical models.The standard modelling approach is,however,prone to missing the ground state atomic configurations associated with energy-lowering reconstructions from the idealised crystallographic environment.Missed ground states compromise the accuracy of calculated properties.To address this issue,we report an approach to navigate the defect configurational landscape using targeted bond distortions and rattling.Application of our workflow to eight materials(CdTe,GaAs,Sb_(2)S_(3),Sb_(2)Se_(3),CeO_(2),In_(2)O_(3),ZnO,anatase-TiO_(2))reveals symmetry breaking in each host crystal that is not found via conventional local minimisation techniques.The point defect distortions are classified by the associated physico-chemical factors.We demonstrate the impact of these defect distortions on derived properties,including formation energies,concentrations and charge transition levels.Our work presents a step forward for quantitative modelling of imperfect solids.
基金This work was primarily funded by the U.S.Department of Energy,Office of Science,Office of Basic Energy Sciences,Materials Sciences and Engineering Division under Contract No.DE-AC02-05-CH11231:Materials Project program KC23MPThis research used resources of the National Energy Research Scientific Computing Center,which is supported by the Office of Science of the U.S.Department of Energy under Contract No.DE-AC02-05-CH11231+1 种基金This work was partially performed under the auspices of the U.S.DOE by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344DB would like to thank Chris G.Van de Walle,Nick Adamski,Andrew Rowberg,and Mark Turiansky along with all of the attendees of the 2018 Gordon Research Conference for Point Defects in Semiconductors for many constructive discussions on this paper’s topic.
文摘Calculations of point defect energetics with Density Functional Theory(DFT)can provide valuable insight into several optoelectronic,thermodynamic,and kinetic properties.These calculations commonly use methods ranging from semi-local functionals with a-posteriori corrections to more computationally intensive hybrid functional approaches.For applications of DFT-based high-throughput computation for data-driven materials discovery,point defect properties are of interest,yet are currently excluded from available materials databases.This work presents a benchmark analysis of automated,semi-local point defect calculations with a-posteriori corrections,compared to 245“gold standard”hybrid calculations previously published.We consider three different a-posteriori correction sets implemented in an automated workflow,and evaluate the qualitative and quantitative differences among four different categories of defect information:thermodynamic transition levels,formation energies,Fermi levels,and dopability limits.We highlight qualitative information that can be extracted from high-throughput calculations based on semi-local DFT methods,while also demonstrating the limits of quantitative accuracy.
