Chen Yuxuan, Tian Bailin, Cheng Zheng, Li Xiaoshan, Huang Min, Sun Yuxia, Liu Shuai, Cheng Xu, Li Shuhua, Ding Mengning
Key Laboratory of Mesoscopic Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China.
Institute of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China.
Angew Chem Int Ed Engl. 2021 Feb 19;60(8):4199-4207. doi: 10.1002/anie.202014072. Epub 2020 Dec 23.
Electrochemical organic synthesis has attracted increasing attentions as a sustainable and versatile synthetic platform. Quantitative assessment of the electro-organic reactions, including reaction thermodynamics, electro-kinetics, and coupled chemical processes, can lead to effective analytical tool to guide their future design. Herein, we demonstrate that electrochemical parameters such as onset potential, Tafel slope, and effective voltage can be utilized as electro-descriptors for the evaluation of reaction conditions and prediction of reactivities (yields). An "electro-descriptor-diagram" is generated, where reactive and non-reactive conditions/substances show distinct boundary. Successful predictions of reaction outcomes have been demonstrated using electro-descriptor diagram, or from machine learning algorithms with experimentally-derived electro-descriptors. This method represents a promising tool for data-acquisition, reaction prediction, mechanistic investigation, and high-throughput screening for general organic electro-synthesis.
电化学有机合成作为一种可持续且通用的合成平台，已引起越来越多的关注。对电有机反应进行定量评估，包括反应热力学、电动力学和耦合化学过程，可产生有效的分析工具来指导其未来设计。在此，我们证明诸如起始电位、塔菲尔斜率和有效电压等电化学参数可作为电描述符，用于评估反应条件和预测反应活性（产率）。生成了一个“电描述符图”，其中反应性和非反应性条件/物质显示出明显的边界。使用电描述符图或基于实验得出的电描述符的机器学习算法，已成功预测了反应结果。该方法是一种很有前景的数据采集、反应预测、机理研究和通用有机电合成高通量筛选工具。
