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Robust ΔSCF calculations with direct energy functional minimization methods and STEP for molecules and materials

Kumar, Chandan; Luber, Sandra (2022). Robust ΔSCF calculations with direct energy functional minimization methods and STEP for molecules and materials. Journal of Chemical Physics, 156(15):154104.

Abstract

The direct energy functional minimization method using the orbital transformation (OT) scheme in the program package CP2K has been employed for Δ self-consistent field (ΔSCF) calculations. The OT method for non-uniform molecular orbitals occupations allows us to apply the ΔSCF method for various kinds of molecules and periodic systems. Vertical excitation energies of heteroaromatic molecules and condensed phase systems, such as solvated ethylene and solvated uracil obeying periodic boundary conditions, are reported using the ΔSCF method. In addition, a Re–phosphate molecule attached to the surface of anatase (TiO2) has been investigated. Additionally, we have implemented a recently proposed state-targeted energy projection ΔSCF algorithm [K. Carter-Fenk and J. M. Herbert, J. Chem. Theory Comput. 16(8), 5067–5082 (2020)] for diagonalization based SCF in CP2K. It is found that the OT scheme provides a smooth and robust SCF convergence for all investigated excitation energies and (non-)periodic systems.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Department of Chemistry
Dewey Decimal Classification:540 Chemistry
Scopus Subject Areas:Physical Sciences > General Physics and Astronomy
Physical Sciences > Physical and Theoretical Chemistry
Uncontrolled Keywords:Physical and Theoretical Chemistry, General Physics and Astronomy
Language:English
Date:21 April 2022
Deposited On:05 Jan 2023 13:07
Last Modified:13 Jan 2025 19:35
Publisher:American Institute of Physics
ISSN:0021-9606
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1063/5.0075927
Project Information:
  • Funder: Swiss National Science Foundation
  • Grant ID: PP00P2 170667
  • Project Title:
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  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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