All Publications

  • Hypophosphite addition to alkenes under solvent-free and non-acidic aqueous conditions. Chemical communications (Cambridge, England) Huang, Z., Chen, Y., Kanan, M. W. 1800


    Hypophosphite adds to alkenes in high yields under solvent-free conditions at elevated temperature, including alpha,beta-unsaturated carboxylates. The reaction proceeds by a radical mediated pathway. Hypophosphite addition is also effective under non-acidic aqueous conditions employing radical initiators. These methods complement other hypophosphite addition reactions and simplify the synthesis of polyfunctional H-phosphinates.

    View details for DOI 10.1039/d1cc06831h

    View details for PubMedID 35060983

  • Electro-Descriptors for the Performance Prediction of Electro-Organic Synthesis ANGEWANDTE CHEMIE-INTERNATIONAL EDITION Chen, Y., Tian, B., Cheng, Z., Li, X., Huang, M., Sun, Y., Liu, S., Cheng, X., Li, S., Ding, M. 2021; 60 (8): 4199-4207


    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.

    View details for DOI 10.1002/anie.202014072

    View details for Web of Science ID 000601056900001

    View details for PubMedID 33180375