Machine Learning Optimization of Non-Kasha Behavior and of Transient Dynamics in Model Retinal Isomerization DOI
Davinder Singh, Chern Chuang, Paul Brumer

et al.

The Journal of Physical Chemistry Letters, Journal Year: 2024, Volume and Issue: 15(51), P. 12543 - 12550

Published: Dec. 16, 2024

Designing a model of retinal isomerization in rhodopsin, the first step vision, that accounts for both experimental transient and stationary state observables is challenging. Here, multiobjective Bayesian optimization employed to refine parameters minimal two-state-two-mode (TM) describing photoisomerization rhodopsin. The optimized predicts excitation wavelength-dependent fluorescence spectra closely align with experimentally observed non-Kasha behavior nonequilibrium steady state. Further, adjustments potential energy surface within TM reduce discrepancies across time domain. Overall, agreement data excellent.

Language: Английский

Machine learning assisted development of Heusler alloys for high magnetic moment DOI
Kai Liu,

Bingxin Ge,

Fangyu Liu

et al.

Computational Materials Science, Journal Year: 2025, Volume and Issue: 250, P. 113692 - 113692

Published: Jan. 20, 2025

Language: Английский

Citations

0
Machine Learning Optimization of Non-Kasha Behavior and of Transient Dynamics in Model Retinal Isomerization DOI
Davinder Singh, Chern Chuang, Paul Brumer

et al.

The Journal of Physical Chemistry Letters, Journal Year: 2024, Volume and Issue: 15(51), P. 12543 - 12550

Published: Dec. 16, 2024

Designing a model of retinal isomerization in rhodopsin, the first step vision, that accounts for both experimental transient and stationary state observables is challenging. Here, multiobjective Bayesian optimization employed to refine parameters minimal two-state-two-mode (TM) describing photoisomerization rhodopsin. The optimized predicts excitation wavelength-dependent fluorescence spectra closely align with experimentally observed non-Kasha behavior nonequilibrium steady state. Further, adjustments potential energy surface within TM reduce discrepancies across time domain. Overall, agreement data excellent.

Language: Английский

Citations

0