<?xml version='1.0' encoding='utf-8'?> <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"> <dc:creator>Sjølin, Benjamin H.</dc:creator> <dc:creator>Jørgensen, Peter B.</dc:creator> <dc:creator>Fedrigucci, Andrea</dc:creator> <dc:creator>Vegge, Tejs</dc:creator> <dc:creator>Bhowmik, Arghya</dc:creator> <dc:creator>Castelli, Ivano E.</dc:creator> <dc:date>2023-05-23</dc:date> <dc:description>We developed and implemented a multi-target multi-fidelity workflow to explore the chemical space of antiperovskite materials with general formula X3BA (X = Li, Na, Mg) and PM-3m space group, searching for stable high-performance solid state electrolytes for all-solid state batteries. The workflow is based on the calculation of thermodynamic and kinetic properties, which include phase and electrochemical stability, semiconducting behaviour, and ionic diffusivity. To accelerate the calculation of the kinetic properties, we use a surrogate model able to predict the transition state structure during ionic diffusion. This reduces the calculation cost by more than one order of magnitude while keeping the mean error within 73 meV compared to the more accurate nudged elastic band method. This method allows us identify 14 materials that agree with the experimentally reported results as some of the best solid state electrolytes. Moreover, this approach is general and chemistry neutral, so can be applied to other battery chemistries and crystal prototypes. We report here the data produced in this work. These results are collected as ASE database. It contains a markdown file that explains the usage and most important data.</dc:description> <dc:identifier>https://archive.materialscloud.org/record/2023.80</dc:identifier> <dc:identifier>doi:10.24435/materialscloud:39-xs</dc:identifier> <dc:identifier>mcid:2023.80</dc:identifier> <dc:identifier>oai:materialscloud.org:1369</dc:identifier> <dc:language>en</dc:language> <dc:publisher>Materials Cloud</dc:publisher> <dc:rights>info:eu-repo/semantics/openAccess</dc:rights> <dc:rights>Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights> <dc:subject>Solid-state Electrolytes</dc:subject> <dc:subject>Antiperovskites</dc:subject> <dc:subject>Autonomous Workflow</dc:subject> <dc:subject>Surrogate Models</dc:subject> <dc:subject>High-throughput Screening</dc:subject> <dc:subject>NEB Calculations</dc:subject> <dc:title>Accelerated workflow for antiperovskite-based solid state electrolytes</dc:title> <dc:type>Dataset</dc:type> </oai_dc:dc>