Gentlest ascent dynamics for calculating first excited state and exploring energy landscape of Kohn-Sham density functionals
Abstract
Here, we develop the gentlest ascent dynamics for Kohn-Sham density functional theory to search for the index-1 saddle points on the energy landscape of the Kohn-Sham density functionals. These stationary solutions correspond to excited states in the ground state functionals. As shown by various examples, the first excited states of many chemical systems are given by these index-1 saddle points. Our novel approach provides an alternative, more robust way to obtain these excited states, compared with the widely used ΔSCF approach. The method can be easily generalized to target higher index saddle points. Our results also reveal the physical interest and relevance of studying the Kohn-Sham energy landscape.
- Authors:
-
- Duke Univ., Durham, NC (United States)
- Duke Univ., Durham, NC (United States); South China Normal Univ., Guangzhou (China)
- Publication Date:
- Research Org.:
- Energy Frontier Research Centers (EFRC), Washington, D.C. (United States). Center for the Computational Design of Functional Layered Materials (CCDM)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES)
- OSTI Identifier:
- 1371102
- Alternate Identifier(s):
- OSTI ID: 1228787
- Grant/Contract Number:
- SC0012575
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Chemical Physics
- Additional Journal Information:
- Journal Volume: 143; Journal Issue: 22; Related Information: CCDM partners with Temple University (lead); Brookhaven National Laboratory; Drexel University; Duke University; North Carolina State University; Northeastern University; Princeton University; Rice University; University of Pennsylvania; Journal ID: ISSN 0021-9606
- Publisher:
- American Institute of Physics (AIP)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; catalysis (heterogeneous); solar (photovoltaic); energy storage (including batteries and capacitors); hydrogen and fuel cells; defects; mechanical behavior; materials and chemistry by design; synthesis (novel materials)
Citation Formats
Li, Chen, Lu, Jianfeng, and Yang, Weitao. Gentlest ascent dynamics for calculating first excited state and exploring energy landscape of Kohn-Sham density functionals. United States: N. p., 2015.
Web. doi:10.1063/1.4936411.
Li, Chen, Lu, Jianfeng, & Yang, Weitao. Gentlest ascent dynamics for calculating first excited state and exploring energy landscape of Kohn-Sham density functionals. United States. https://doi.org/10.1063/1.4936411
Li, Chen, Lu, Jianfeng, and Yang, Weitao. Wed .
"Gentlest ascent dynamics for calculating first excited state and exploring energy landscape of Kohn-Sham density functionals". United States. https://doi.org/10.1063/1.4936411. https://www.osti.gov/servlets/purl/1371102.
@article{osti_1371102,
title = {Gentlest ascent dynamics for calculating first excited state and exploring energy landscape of Kohn-Sham density functionals},
author = {Li, Chen and Lu, Jianfeng and Yang, Weitao},
abstractNote = {Here, we develop the gentlest ascent dynamics for Kohn-Sham density functional theory to search for the index-1 saddle points on the energy landscape of the Kohn-Sham density functionals. These stationary solutions correspond to excited states in the ground state functionals. As shown by various examples, the first excited states of many chemical systems are given by these index-1 saddle points. Our novel approach provides an alternative, more robust way to obtain these excited states, compared with the widely used ΔSCF approach. The method can be easily generalized to target higher index saddle points. Our results also reveal the physical interest and relevance of studying the Kohn-Sham energy landscape.},
doi = {10.1063/1.4936411},
journal = {Journal of Chemical Physics},
number = 22,
volume = 143,
place = {United States},
year = {Wed Dec 09 00:00:00 EST 2015},
month = {Wed Dec 09 00:00:00 EST 2015}
}
Web of Science
Figures / Tables:
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