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预测自旋相关过程的动力学和动态过程。

Predicting Kinetics and Dynamics of Spin-Dependent Processes.

作者信息

Dergachev Ilya D, Dergachev Vsevolod D, Rooein Mitra, Mirzanejad Amir, Varganov Sergey A

机构信息

Department of Chemistry, University of Nevada, Reno, 1664 N. Virginia Street, Reno, Nevada 89557-0216, United States.

出版信息

Acc Chem Res. 2023 Apr 4;56(7):856-866. doi: 10.1021/acs.accounts.2c00843. Epub 2023 Mar 16.

Abstract

ConspectusPredicting mechanisms and rates of nonadiabatic spin-dependent processes including photoinduced intersystem crossings, thermally activated spin-forbidden reactions, and spin crossovers in metal centers is a very active field of research. These processes play critical roles in transition-metal-based and metalloenzymatic catalysis, molecular magnets, light-harvesting materials, organic light-emitting diodes, photosensitizers for photodynamic therapy, and many other applications. Therefore, accurate modeling of spin-dependent processes in complex systems and on different time scales is important for many problems in chemistry, biochemistry, and materials sciences.Nonadiabatic statistical theory (NAST) and nonadiabatic molecular dynamics (NAMD) are two complementary approaches to modeling the kinetics and dynamics of spin-dependent processes. NAST predicts the probabilities and rate constants of nonradiative transitions between electronic states with different spin multiplicities using molecular properties at only few critical points on the potential energy surfaces (PESs), including the reactant minimum and the minimum energy crossing point (MECP) between two spin states. This makes it possible to obtain molecular properties for NAST calculations using accurate but often computationally expensive electronic structure methods, which is critical for predicting the rate constants of spin-dependent processes. Alternatively, NAST can be used to study spin-dependent processes in very large complex molecular systems using less computationally expensive electronic structure methods. The nuclear quantum effects, such as zero-point vibrational energy, tunneling, and interference between reaction paths can be easily incorporated. However, the statistical and local nature of NAST makes it more suitable for large systems and slow kinetics. In contrast, NAMD explores entire PESs of interacting electronic states, making it ideal for modeling fast barrierless spin-dependent processes. Because the knowledge of large portions of PESs is often needed, the simulations require a very large number of electronic structure calculations, which limits the NAMD applicability to relatively small molecular systems and ultrafast kinetics.In this Account, we discuss our contribution to the development of the NAST and NAMD approaches for predicting the rates and mechanism of spin-dependent processes. First, we briefly describe our NAST and NAMD implementations. The NAST implementation is an extension of the transition state theory to the processes involving two crossing potential energy surfaces of different spin multiplicities. The NAMD approach includes the trajectory surface hopping (TSH) and multiple spawning (AIMS) methods. Second, we discuss several applications of NAST and NAMD to model spin-dependent processes in different systems. The NAST applicability to large complex systems is demonstrated by the studies of the spin-forbidden isomerization of the active sites of metal-sulfur proteins. Our implementation of the MECP search algorithm within the fully fragment molecular orbital method allows applying NAST to systems with thousands of atoms, such as the solvated protein rubredoxin. Applications of NAMD to ultrafast spin-dependent processes are represented by the generalized AIMS simulations utilizing the fast GPU-based TeraChem electronic structure program to gain insight into the complex photoexcited state relaxation in 2-cyclopentenone.

摘要

概述

预测非绝热自旋相关过程的机制和速率,包括光诱导的系间窜越、热激活的自旋禁阻反应以及金属中心的自旋交叉,是一个非常活跃的研究领域。这些过程在基于过渡金属的催化、金属酶催化、分子磁体、光捕获材料、有机发光二极管、光动力疗法的光敏剂以及许多其他应用中起着关键作用。因此,在复杂系统中以及不同时间尺度上对自旋相关过程进行精确建模,对于化学、生物化学和材料科学中的许多问题都很重要。

非绝热统计理论(NAST)和非绝热分子动力学(NAMD)是两种用于模拟自旋相关过程动力学和动态的互补方法。NAST仅使用势能面(PES)上少数几个关键点(包括反应物最低点和两个自旋态之间的最小能量交叉点(MECP))处的分子性质,来预测具有不同自旋多重性的电子态之间非辐射跃迁的概率和速率常数。这使得使用精确但通常计算成本高昂的电子结构方法来获得用于NAST计算的分子性质成为可能,这对于预测自旋相关过程的速率常数至关重要。或者,NAST可用于使用计算成本较低的电子结构方法研究非常大的复杂分子系统中的自旋相关过程。核量子效应,如零点振动能、隧穿和反应路径之间的干涉,可以很容易地纳入其中。然而,NAST的统计和局部性质使其更适合于大系统和慢动力学。相比之下,NAMD探索相互作用电子态的整个PES,使其非常适合于对快速无势垒自旋相关过程进行建模。由于通常需要了解大部分PES,模拟需要大量的电子结构计算,这将NAMD的适用性限制在相对较小的分子系统和超快动力学上。

在本综述中,我们讨论了我们对开发用于预测自旋相关过程速率和机制的NAST和NAMD方法所做的贡献。首先,我们简要描述我们的NAST和NAMD实现。NAST实现是将过渡态理论扩展到涉及两个不同自旋多重性交叉势能面的过程。NAMD方法包括轨迹表面跳跃(TSH)和多重衍生(AIMS)方法。其次,我们讨论了NAST和NAMD在不同系统中对自旋相关过程进行建模的几个应用。通过对金属硫蛋白活性位点的自旋禁阻异构化的研究,证明了NAST对大型复杂系统的适用性。我们在完全片段分子轨道方法中实现的MECP搜索算法允许将NAST应用于具有数千个原子的系统,如溶剂化的蛋白质红氧还蛋白。利用基于快速GPU的TeraChem电子结构程序进行的广义AIMS模拟代表了NAMD在超快自旋相关过程中的应用,以深入了解2 - 环戊烯酮中复杂的光激发态弛豫。

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