High-throughput computation of electric polarization in solids via Berry flux diagonalization
Abstract Electric polarization in the absence of an externally applied electric field is a key property of polar materials, but the standard interpolation-based ab initio approach to compute polarization differences within the modern theory of polarization presents challenges for automated high-throughput calculations. Berry flux diagonalization [J. Bonini et al., Phys. Rev. B 102 , 045141 (2020)] has been proposed as an efficient and reliable alternative, though it has yet to be widely deployed. Here, we assess Berry flux diagonalization using ab initio calculations of a large set of materials, introducing and validating heuristics that ensure branch alignment with a minimal number of intermediate interpolated structures. Our automated implementation of Berry flux diagonalization succeeds in cases where prior interpolation-based workflows fail due to band-gap closures or branch ambiguities. Benchmarking with ab initio calculations of 176 candidate ferroelectrics, we demonstrate the efficacy of the approach on a broad range of insulating materials and obtain accurate effective polarization values with fewer interpolated structures than prior automated interpolation-based workflows. Our real-space heuristics that can predict gauge stability a priori from ionic displacements enable a general automated framework for reliable polarization calculations and efficient high-throughput screening of chemically and structurally diverse polar insulators. These results establish Berry flux diagonalization as a robust and efficient method to compute the effective polarization of solids and to accelerate the data-driven discovery of functional polar materials.
Authors
- Abigail N. Poteshman (ORCID: https://orcid.org/0000-0002-4873-4826)
- Francesco Ricci (ORCID: https://orcid.org/0000-0002-2677-7227)
- Jeffrey B. Neaton
Institutions
- Argonne National Laboratory (US)
- Lawrence Berkeley National Laboratory (US)
- University of Chicago (US)
- Kavli Energy NanoScience Institute (US)
- Applied Mathematics (United States) (US)
- Grand Charleroi Hospital (BE)
- University of California, Berkeley (US)
- UCLouvain (BE)
Publication Details
- Journal
- npj Computational Materials
- Published
- 2026-01-20
- DOI
- https://doi.org/10.1038/s41524-025-01955-1
- Primary Topic
- Inorganic Chemistry and Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- U.S. Department of Energy
- National Energy Research Scientific Computing Center
- European Commission
- Office of Science
- Basic Energy Sciences
- Lawrence Berkeley National Laboratory