Institute of Organic Chemistry, RWTH Aachen University , Landoltweg 1, 52074 Aachen, Germany.
Laboratory for Organic Chemistry, ETH Zürich , Vladimir-Prelog-Weg 3, 8093 Zürich, Switzerland.
Acc Chem Res. 2016 Jun 21;49(6):1311-9. doi: 10.1021/acs.accounts.6b00068. Epub 2016 May 12.
Computational chemistry has become an established tool for the study of the origins of chemical phenomena and examination of molecular properties. Because of major advances in theory, hardware and software, calculations of molecular processes can nowadays be done with reasonable accuracy on a time-scale that is competitive or even faster than experiments. This overview will highlight broad applications of computational chemistry in the study of organic and organometallic reactivities, including catalytic (NHC-, Cu-, Pd-, Ni-catalyzed) and noncatalytic examples of relevance to organic synthesis. The selected examples showcase the ability of computational chemistry to rationalize and also predict reactivities of broad significance. A particular emphasis is placed on the synergistic interplay of computations and experiments. It is discussed how this approach allows one to (i) gain greater insight than the isolated techniques, (ii) inspire novel chemistry avenues, and (iii) assist in reaction development. Examples of successful rationalizations of reactivities are discussed, including the elucidation of mechanistic features (radical versus polar) and origins of stereoselectivity in NHC-catalyzed reactions as well as the rationalization of ligand effects on ligation states and selectivity in Pd- and Ni-catalyzed transformations. Beyond explaining, the synergistic interplay of computation and experiments is then discussed, showcasing the identification of the likely catalytically active species as a function of ligand, additive, and solvent in Pd-catalyzed cross-coupling reactions. These may vary between mono- or bisphosphine-bound or even anionic Pd complexes in polar media in the presence of coordinating additives. These fundamental studies also inspired avenues in catalysis via dinuclear Pd(I) cycles. Detailed mechanistic studies supporting the direct reactivity of Pd(I)-Pd(I) with aryl halides as well as applications of air-stable dinuclear Pd(I) catalysts are discussed. Additional combined experimental and computational studies are described for alternative metals, these include the discussion of the factors that control C-H versus C-C activation in the aerobic Cu-catalyzed oxidation of ketones, and ligand and additive effects on the nature and favored oxidation state of the active catalyst in Ni-catalyzed trifluoromethylthiolations of aryl chlorides. Examples of successful computational reactivity predictions along with experimental verifications are then presented. This includes the design of a fluorinated ligand [(CF3)2P(CH2)2P(CF3)2] for the challenging reductive elimination of ArCF3 from Pd(II) as well as the guidance of substrate scope (functional group tolerance and suitable leaving group) in the Ni-catalyzed trifluoromethylthiolation of C(sp(2))-O bonds. In summary, this account aims to convey the benefits of integrating computational studies in experimental research to increase understanding of observed phenomena and guide future experiments.
计算化学已成为研究化学现象起源和考察分子性质的一种成熟工具。由于理论、硬件和软件方面的重大进展,现今可以在具有竞争力甚至更快的时间尺度上对分子过程进行合理精确的计算。本综述将重点介绍计算化学在有机和有机金属反应性研究中的广泛应用,包括催化(NHC、Cu、Pd、Ni 催化)和非催化的与有机合成相关的例子。所选的例子展示了计算化学在合理化和预测广泛意义上的反应性方面的能力。特别强调了计算和实验的协同作用。讨论了这种方法如何使人们能够:(i)获得比孤立技术更深入的见解;(ii)激发新的化学途径;(iii)帮助反应的发展。讨论了成功合理化反应性的例子,包括阐明 NHC 催化反应中的反应机理特征(自由基与极性)和立体选择性的起源,以及配体对 Pd 和 Ni 催化转化中的键合状态和选择性的影响的合理化。除了解释之外,还讨论了计算和实验的协同作用,展示了作为配体、添加剂和溶剂函数的 Pd 催化交叉偶联反应中可能的催化活性物种的识别。在存在配位添加剂的情况下,这些可能在极性介质中在单或双膦配体结合的或甚至阴离子 Pd 配合物之间变化。这些基础研究还激发了通过双核 Pd(I)循环的催化途径。讨论了支持 Pd(I)-Pd(I)与芳基卤化物直接反应的详细机理研究以及空气稳定双核 Pd(I)催化剂的应用。还描述了用于替代金属的其他组合实验和计算研究,包括讨论控制酮的有氧 Cu 催化氧化中 C-H 与 C-C 活化的因素,以及配体和添加剂对 Ni 催化芳基氯的三氟甲基化中活性催化剂的性质和有利氧化态的影响。然后介绍了成功的计算反应性预测以及实验验证的例子。这包括设计一种氟化配体[(CF3)2P(CH2)2P(CF3)2],用于从 Pd(II)中具有挑战性的还原消除 ArCF3,以及在 Ni 催化的 C(sp(2))-O 键的三氟甲基化中指导底物范围(官能团容忍度和合适的离去基团)。总之,本综述旨在传达将计算研究纳入实验研究中的好处,以增加对观察到的现象的理解并指导未来的实验。