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一个分子电机中的超快光控制旋转,通过基于机器学习的非adiabatic动力学模拟进行了研究
Haoyang Xu1, Boyuan Zhang1, Yuanda Tao1
1State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China.
The journal of physical chemistry. A
|September 6, 2023
概括
这项研究表明,类似的激发能量和快捷的光诱导转换使氨酸基分子电机中的全光化学旋转成为可能,取代了热步骤. 这项工作加速了复杂的光化学系统的模拟.
科学领域:
- 摄影化学的使用
- 计算化学的计算化学
- 分子机器分子机器
背景情况:
- 过度拥挤的基分子电机通常依赖热螺旋逆转 (THI) 进行旋转,受到高基态障碍的限制.
- 最近的氨酸基电机实现全光化学旋转,但该机制需要进一步阐明.
- 非协同分子动力学 (NAMD) 模拟对于研究光化学反应至关重要,但对于大型系统来说,计算成本昂贵.
研究的目的:
- 阐明基于氨酸的分子电机的光化学反应机制.
- 用先进的计算方法探索反应路径.
- 开发一种高效的方法来模拟复杂的光化学系统.
主要方法:
- 旋转翻转时间依赖密度函数理论 (SF-TDDFT) 的计算.
- 基于机器学习 (ML) 的非adiabatic分子动力学 (NAMD) 模拟.
- 对潜在能量表面 (PES) 和形交叉点 (CI) 的分析.
主要成果:
- 在四个异构体中具有相似的激发能量是实现全光化学旋转的关键.
- 不稳定异构体之间的直接光诱导转换绕过了热螺旋逆转 (THI) 步骤.
- 快捷路径与光异构化共享一个形交叉点 (CI),促进了该过程.
结论:
- 该研究提供了对氨酸基发动机中全光化学旋转的详细机制理解.
- 机器学习显著加速NAMD模拟大型光化学系统.
- 这种方法为研究复杂的光化学反应和分子电机提供了一种实用方法.
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