Lee Sanha, Goodman Jonathan M
Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK.
Org Biomol Chem. 2021 May 5;19(17):3940-3947. doi: 10.1039/d1ob00234a.
In recent years, a growing number of organic reactions in the literature have shown selectivity controlled by reaction dynamics rather than by transition state theory. Such reactions are difficult to analyse because the transition state theory approach often does not capture the subtlety of the energy landscapes the compounds traverse and, therefore, cannot accurately predict the selectivity. We present an algorithm that can predict the major product and selectivity for a wide range of potential energy surfaces where the product distribution is influenced by reaction dynamics. The method requires as input calculation of the transition states, the intermediate (if present) and the product geometries. The algorithm is quick and simple to run and, except for two reactions with long alkyl chains, calculates selectivity more accurately than transition state theory alone.
近年来，文献中越来越多的有机反应显示出选择性是由反应动力学而非过渡态理论控制的。这类反应难以分析，因为过渡态理论方法往往无法捕捉化合物所穿越的能量景观的微妙之处，因此无法准确预测选择性。我们提出了一种算法，该算法可以预测在广泛的势能面上的主要产物和选择性，在这些势能面上产物分布受反应动力学影响。该方法需要输入过渡态、中间体（如果存在）和产物几何结构的计算结果。该算法运行快速且简单，除了两个带有长烷基链的反应外，其计算选择性的准确性高于单独使用过渡态理论。
