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Automatic Migration Path Exploration for Multivalent Battery Cathodes using Geometrical Descriptors

Felix T. Bölle, Arghya Bhowmik, Tejs Vegge, Juan Maria García Lastra, Ivano E. Castelli

2021Batteries & Supercaps18 citationsDOIOpen Access PDF

Abstract

Abstract Stable and fast ionic conductors for magnesium cathode materials have the prospect of enabling high energy density batteries beyond current Lithium‐ion technologies. So far, only a few candidate materials have been identified leading to data only being scarcely available to the community. Here, we present a systematic study, in the framework of Density Functional Theory, including the estimation of the migration barrier for 16 materials through employing Nudged Elastic Band (NEB) calculations. By introducing a path finder algorithm based on the idea of Voronoi tessellations, we show that an estimate of the transition state configuration can be extracted automatically prior to running NEB‐calculations. Using geometrical descriptors in combination with a principal component analysis it is possible to further sub‐group the migration paths. This approach also extends to materials which are not part of the study, making it a viable approach to more efficiently explore crystal structures with distinguishable migration characteristics.

Topics & Concepts

Path (computing)CathodeComputer scienceBattery (electricity)Voronoi diagramPrincipal component analysisState (computer science)Electrical conductorTrajectoryEnergy (signal processing)Energy densityScheme (mathematics)AlgorithmBlock (permutation group theory)Materials scienceComponent (thermodynamics)Current densityElectronic engineeringCurrent (fluid)Density estimationElectrical impedancePotential energySimulationFeature (linguistics)EngineeringBiological systemDensity functional theoryMachine Learning in Materials ScienceX-ray Diffraction in CrystallographyAdvancements in Battery Materials
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