First-principles Hubbard parameters with automated and reproducible workflows
We introduce an automated, flexible framework (aiida-hubbard) to self-consistently calculate Hubbard <i>U</i> and <i>V</i> parameters from first-principles. By leveraging density-functional perturbation theory, the computation of the Hubbard parameters is efficiently parallelized using multiple concurrent and inexpensive primitive cell calculations. Furthermore, the intersite <i>V</i> parameters are defined on-the-fly during the iterative procedure to account for atomic relaxations and diverse coordination environments. We devise a novel, code-agnostic data structure to store Hubbard related information together with the atomistic structure, to enhance the reproducibility of Hubbard-corrected calculations. We demonstrate the scalability and reliability of the framework by computing in high-throughput fashion the self-consistent onsite <i>U</i> and intersite <i>V</i> parameters for 115 Li-containing bulk solids with up to 32 atoms in the unit cell. Our analysis of the Hubbard parameters calculated reveals a significant correlation of the onsite <i>U</i> values on the oxidation state and coordination environment of the atom on which the Hubbard manifold is centered, while intersite <i>V</i> values exhibit a general decay with increasing interatomic distance. We find, e.g., that the numerical values of <i>U</i> for the 3d orbitals of Fe and Mn can vary up to 3 eV and 6 eV, respectively; their distribution is characterized by typical shifts of about 0.5 eV and 1.0 eV upon change in oxidation state, or local coordination environment. For the intersite <i>V</i> a narrower spread is found, with values ranging between 0.2 eV and 1.6 eV when considering transition metal and oxygen interactions. This framework paves the way for the exploration of redox materials chemistry and high-throughput screening of <i>d</i> and <i>f</i> compounds across diverse research areas, including the discovery and design of novel energy storage materials, as well as other technologically-relevant applications.
Authors
- Nicola Marzari (ORCID: https://orcid.org/0000-0002-9764-0199)
- Lorenzo Bastonero (ORCID: https://orcid.org/0000-0001-9374-1876)
- Marnik Bercx (ORCID: https://orcid.org/0000-0001-8470-1012)
- Sebastiaan P. Huber (ORCID: https://orcid.org/0000-0001-5845-8880)
- Iurii Timrov (ORCID: https://orcid.org/0000-0002-6531-9966)
- Eric Macke (ORCID: https://orcid.org/0009-0003-4546-0887)
- Cristiano Malica
Institutions
- University of Bremen (DE)
- Paul Scherrer Institute (CH)
- École Polytechnique Fédérale de Lausanne (CH)
Publication Details
- Journal
- npj Computational Materials
- Published
- 2025-06-16
- DOI
- https://doi.org/10.1038/s41524-025-01685-4
- Citations
- 6
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 25.01
Funders
- National Science Foundation
- Deutsche Forschungsgemeinschaft
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- Universität Bremen
- Centro Svizzero di Calcolo Scientifico
- National Supercomputing Centre Singapore
- Staatssekretariat für Bildung, Forschung und Innovation
- National Center of Competence in Research Materials’ Revolution: Computational Design and Discovery of Novel Materials