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Published on: May 27, 2020
Gaussian Charge-Based Electrostatic Embedding Scheme for Solid-State Excited-State Modeling
Alexandre Huguet1, Ilaria Ciofini1, Frédéric Labat1
1Institute of Chemistry for Life and Health Sciences, Chemical Theory and Modelling Group, Chimie ParisTech, PSL University, CNRS, F-75005 Paris, France.
We developed a Gaussian charge-based (GC) electrostatic embedding scheme for modeling excited-state properties in solids. This robust method improves upon point-charge (PC) models, preventing unphysical electron density issues and offering accurate results for crystalline materials.
Area of Science:
- Computational Chemistry
- Materials Science
- Solid-State Physics
Background:
- Electrostatic embedding schemes are crucial for modeling excited-state properties of crystalline materials affordably and accurately.
- Traditional point-charge (PC) formalisms can suffer from numerical instabilities and unphysical electron density behavior.
Purpose of the Study:
- Introduce and validate a Gaussian charge-based (GC) electrostatic embedding scheme for solid-state excited-state calculations.
- Address limitations of PC formalisms by offering a more physically sound approach.
Main Methods:
- Developed a GC electrostatic embedding scheme utilizing analytical Ewald lattice summations.
- Validated the scheme by comparing electrostatic potentials from PC and GC formalisms across 530 crystalline structures.
- Proposed a criterion based on interatomic distance to optimize the Gaussian width parameter.
Main Results:
- Achieved excellent agreement between PC and GC electrostatic potentials with an optimized Gaussian width parameter.
- Demonstrated that GC embedding avoids the excessive electron density contraction seen with PC methods.
- Obtained excitation energies for crystalline imidazole using GC embedding that agree well with GW-BSE and hybrid calculations.
Conclusions:
- The proposed GC electrostatic embedding scheme is a robust and physically sound alternative to PC models for excited-state calculations in solids.
- GC embedding offers a promising framework for future methodological advancements and practical applications in embedded excited-state calculations.
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