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

и другие.

The Journal of Physical Chemistry Letters, Год журнала: 2024, Номер 15(51), С. 12543 - 12550

Опубликована: Дек. 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.

Язык: Английский

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

Bingxin Ge,

Fangyu Liu

и другие.

Computational Materials Science, Год журнала: 2025, Номер 250, С. 113692 - 113692

Опубликована: Янв. 20, 2025

Язык: Английский

Процитировано

1
Machine Learning Optimization of Non-Kasha Behavior and of Transient Dynamics in Model Retinal Isomerization DOI
Davinder Singh, Chern Chuang, Paul Brumer

и другие.

The Journal of Physical Chemistry Letters, Год журнала: 2024, Номер 15(51), С. 12543 - 12550

Опубликована: Дек. 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.

Язык: Английский

Процитировано

0