Accurate and efficient protocols for high-throughput first-principles materials simulations
Abstract Advancements in theoretical and algorithmic approaches, workflow engines, and an ever-increasing computational power have enabled a novel paradigm for materials discovery through first-principles high-throughput simulations. A major challenge in these efforts is to automate the selection of parameters used by simulation codes to deliver 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. For this goal, we develop criteria to reliably estimate average errors on total energies, forces, and other properties as a function of the desired computational efficiency, while consistently controlling k -point sampling errors. The present results provide automated protocols (named standard solid-state protocols or SSSPr) for selecting optimized parameters based on different choices of precision and efficiency tradeoffs. These are available through open-source tools that range from interactive input generators for DFT codes to high-throughput workflows.
Authors
- Flaviano José dos Santos (ORCID: https://orcid.org/0000-0003-0957-6869)
- Davide Grassano (ORCID: https://orcid.org/0000-0001-8821-6452)
- Giovanni Pizzi
- Nicola Marzari
- Marnik Bercx
- Gabriel de Miranda Nascimento
Publication Details
- Journal
- npj Computational Materials
- Published
- 2026-04-29
- DOI
- https://doi.org/10.1038/s41524-026-02097-8
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00