Yuan Mingbin, Gutierrez Osvaldo
University of Maryland, College Park.
Wiley Interdiscip Rev Comput Mol Sci. 2022 May-Jun;12(3). doi: 10.1002/wcms.1573. Epub 2021 Sep 21.
The merging of photoredox and nickel catalysis has revolutionized the field of C-C cross-coupling. However, in comparison to the development of synthetic methods, detailed mechanistic investigations of these catalytic systems are lagging. To improve the mechanistic understanding, computational tools have emerged as powerful tools to elucidate the factors controlling reactivity and selectivity in these complex catalytic transformations. Based on the reported computational studies, it appears that the mechanistic picture of catalytic systems is not generally applicable, but is rather dependent on the specific choice of substrate, ligands, photocatalysts, etc. Given the complexity of these systems, the need for more accurate computational methods, readily available and user-friendly dynamics simulation tools, and data-driven approaches is clear in order to understand at the molecular level the mechanisms of these transformations. In particular, we anticipate that such improvement of theoretical methods will become crucial to advance the understanding of excited-state properties and dynamics of key species, as well as to enable faster and unbiased exploration of reaction pathways. Further, with greater collaboration between computational, experimental, and spectroscopic communities, the mechanistic investigation of photoredox/Ni dual-catalytic reactions is expected to thrive quickly, facilitating the design of novel catalytic systems and promoting our understanding of the reaction selectivity.
光氧化还原催化与镍催化的结合彻底改变了C-C交叉偶联领域。然而,与合成方法的发展相比,对这些催化体系的详细机理研究滞后。为了增进对机理的理解,计算工具已成为阐明这些复杂催化转化中控制反应性和选择性的因素的有力工具。根据已报道的计算研究,催化体系的机理似乎并不普遍适用,而是取决于底物、配体、光催化剂等的具体选择。鉴于这些体系的复杂性,显然需要更精确的计算方法、易于获得且用户友好的动力学模拟工具以及数据驱动的方法,以便在分子水平上理解这些转化的机理。特别是,我们预计理论方法的这种改进对于推进对关键物种激发态性质和动力学的理解,以及实现对反应途径的更快且无偏差的探索将变得至关重要。此外,随着计算、实验和光谱学界之间的更多合作,光氧化还原/镍双催化反应的机理研究有望迅速蓬勃发展,促进新型催化体系的设计并增进我们对反应选择性的理解。