Institute of Chemistry, Academia Sinica, 128 Section 2 Academia Road, Nankang, Taipei 115, Taiwan.
Physics Division, National Center for Theoretical Sciences, 1, Section 4, Roosevelt Road, Taipei 106, Taiwan.
J Chem Phys. 2023 Jul 21;159(3). doi: 10.1063/5.0155377.
Electron transfer (ET) is a fundamental process in chemistry and biochemistry, and electronic coupling is an important determinant of the rate of ET. However, the electronic coupling is sensitive to many nuclear degrees of freedom, particularly those involved in intermolecular movements, making its characterization challenging. As a result, dynamic disorder in electron transfer coupling has rarely been investigated, hindering our understanding of charge transport dynamics in complex chemical and biological systems. In this work, we employed molecular dynamic simulations and machine-learning models to study dynamic disorder in the coupling of hole transfer between neighboring ethylene and naphthalene dimer. Our results reveal that low-frequency modes dominate these dynamics, resulting primarily from intermolecular movements such as rotation and translation. Interestingly, we observed an increasing contribution of translational motion as temperature increased. Moreover, we found that coupling is sub-Ohmic in its spectral density character, with cut-off frequencies in the range of 102 cm-1. Machine-learning models allow direct study of dynamics of electronic coupling in charge transport with sufficient ensemble trajectories, providing further new insights into charge transporting dynamics.
电子转移（ET）是化学和生物化学中的一个基本过程，电子耦合是 ET 速率的重要决定因素。然而，电子耦合对许多核自由度很敏感，特别是涉及分子间运动的自由度，这使得其特征描述具有挑战性。因此，电子转移耦合中的动态无序很少被研究，这阻碍了我们对复杂化学和生物系统中电荷输运动力学的理解。在这项工作中，我们采用分子动力学模拟和机器学习模型来研究相邻乙烯和萘二聚体之间空穴转移耦合中的动态无序。我们的结果表明，低频模式主导了这些动力学，主要来自分子间的运动，如旋转和平移。有趣的是，我们观察到随着温度的升高，平移运动的贡献增加。此外，我们发现耦合在其谱密度特征上是亚欧姆的，截止频率在 102cm-1 的范围内。机器学习模型允许在具有足够系综轨迹的情况下直接研究电荷输运中电子耦合的动力学，为电荷输运动力学提供了进一步的新见解。
