Optimization algorithm for the generation of ONCV pseudopotentials
Open accessAbstract
We present an optimization algorithm to construct pseudopotentials and use it to generate a set of Optimized Norm-Conserving Vanderbilt (ONCV) pseudopotentials for elements up to Z=83 (Bi) (excluding Lanthanides). We introduce a quality function that assesses the agreement of a pseudopotential calculation with all-electron FLAPW results, and the necessary plane-wave energy cutoff. This quality function allows us to use a Nelder–Mead optimization algorithm on a training set of materials to optimize the input parameters of the pseudopotential construction for most of the periodic table. We control the accuracy of the resulting pseudopotentials on a test set of materials independent of the training set. We find that the automatically constructed pseudopotentials (http://www.quantum-simulation.org) provide a good agreement with the all-electron results obtained using the FLEUR code with a plane-wave energy cutoff of approximately 60 Ry.
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All tested PSP libraries are based on the PBE GGA exchange-correlation functional and include norm-conserving, ultrasoft, and projector-augmented wave pseudization approaches.
“All the tested PSP libraries are based on the generalized gradient approximation (GGA) for the exchangecorrelation functional of Perdew, Burke and Ernzerhof (PBE) [8] and they include the three main pseudization approaches [12]: norm-conserving (NC) [13], ultrasoft (US) [14] and projector-augmented wave (PAW) [15].”
From Precision and efficiency in solid-state pseudopotential calculations (2018) · cites this paper as [13]
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- Authors
- Schlipf, M., & Gygi, F.
- Affiliations
- University of California, Davis (US)
- Corresponding author
- Schlipf, Martin
- Venue
- Computer Physics Communications
- Publisher
- Elsevier BV
- Published
- 2015-11
- Volume
- 196
- Pages
- 36-44
- ISSN
- 0010-4655 (ISSN-L)
- OpenAlex
- W1695703141
- Cited by
- 1,300
- References
- 27
- Citations by year
- 2026: 145 · 2025: 193 · 2024: 158 · 2023: 147 · 2022: 155 · 2021: 141 · 2020: 120 · 2019: 109 · 2018: 80 · 2017: 39 · 2016: 11 · 2015: 2
- FWCI
- 22.33
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Computer Physics Communications (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Office of Science (DE-AC02-06CH11357)
- Argonne National Laboratory
- U.S. Department of Energy (DOE-BES DE-SC0008938)
- Topics
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Advanced Chemical Physics Studies
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Physical Sciences › Engineering › Mechanical Engineering › Thermodynamic and Structural Properties of Metals and Alloys
- Keywords
- norm-conserving pseudopotentials, Nelder-Mead algorithm, quality function, FLAPW, FLEUR, periodic table
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