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Artificial-Intelligence-Enhanced On-the-Fly Simulation of Nonlinear Time-Resolved Spectra.
Pios, Sebastian V; Gelin, Maxim F; Ullah, Arif; Dral, Pavlo O; Chen, Lipeng.
  • Pios SV; Zhejiang Laboratory, Hangzhou, Zhejiang 311100, People's Republic of China.
  • Gelin MF; School of Science, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, People's Republic of China.
  • Ullah A; School of Physics and Optoelectronic Engineering, Anhui University, Hefei, Anhui 230601, People's Republic of China.
  • Dral PO; State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, and Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen Uni
  • Chen L; Zhejiang Laboratory, Hangzhou, Zhejiang 311100, People's Republic of China.
J Phys Chem Lett ; 15(9): 2325-2331, 2024 Mar 07.
Article en En | MEDLINE | ID: mdl-38386692
ABSTRACT
Time-resolved spectroscopy is an important tool for unraveling the minute details of structural changes in molecules of biological and technological significance. The nonlinear femtosecond signals detected for such systems must be interpreted, but it is a challenging task for which theoretical simulations are often indispensable. Accurate simulations of transient absorption or two-dimensional electronic spectra are, however, computationally very expensive, prohibiting the wider adoption of existing first-principles methods. Here, we report an artificial-intelligence-enhanced protocol to drastically reduce the computational cost of simulating nonlinear time-resolved electronic spectra, which makes such simulations affordable for polyatomic molecules of increasing size. The protocol is based on the doorway-window approach for the on-the-fly surface-hopping simulations. We show its applicability for the prototypical molecule of pyrazine for which it produces spectra with high precision with respect to ab initio reference while cutting the computational cost by at least 95% compared to pure first-principles simulations.

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article