Accurate and efficient protocols for high-throughput first-principles materials simulations

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<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>de Miranda Nascimento, Gabriel</dc:creator>
  <dc:creator>José dos Santos, Flaviano</dc:creator>
  <dc:creator>Bercx, Marnik</dc:creator>
  <dc:creator>Pizzi, Giovanni</dc:creator>
  <dc:creator>Marzari, Nicola</dc:creator>
  <dc:date>2025-04-08</dc:date>
  <dc:description>A major challenge in first-principles high-throughput materials simulations is automating the selection of parameters used by simulation codes in a way that robustly ensures numerical precision and computational efficiency. Here, we propose a rigorous methodology to assess the quality of self-consistent DFT calculations with respect to smearing and k-point sampling across a wide range of crystalline materials. To achieve this, we develop criteria to reliably control average errors in total energies, forces, and other properties as a function of the desired computational efficiency, while consistently suppressing uncontrollable k-point sampling errors. Our results provide automated protocols for selecting optimized parameters based on different precision and efficiency tradeoffs. This archive contains all data related to the material structures and calculation workflows developed in this work.</dc:description>
  <dc:identifier>https://materialscloud-archive-failover.cineca.it/record/2025.55</dc:identifier>
  <dc:identifier>doi:10.24435/materialscloud:8t-jj</dc:identifier>
  <dc:identifier>mcid:2025.55</dc:identifier>
  <dc:identifier>oai:materialscloud.org:2562</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>EPFL</dc:subject>
  <dc:subject>MARVEL</dc:subject>
  <dc:subject>high-throughput workflows</dc:subject>
  <dc:subject>protocols</dc:subject>
  <dc:subject>Quantum ESPRESSO</dc:subject>
  <dc:title>Accurate and efficient protocols for high-throughput first-principles materials simulations</dc:title>
  <dc:type>Dataset</dc:type>
</oai_dc:dc>