Energy-, time-, and labor-saving synthesis of α-ketiminophosphonates: machine-learning-assisted simultaneous multiparameter screening for electrochemical oxidation

Abstract

A highly efficient synthesis of α-ketiminophosphonates has been established for the electrochemical oxidation of α-amino phosphonates with the utilization of machine-learning-assisted simultaneous multiparameter screening. After brief experimental screening, the Bayesian optimization with the experimental data (up to 12 entries) could rapidly predict the optimal conditions for the synthesis of α-ketiminophosphonates and sulfonyl ketimines with aryl and alkyl groups. The obtained α-ketiminophosphonates could be converted into highly functionalized α-amino acid analogues with a tetrasubstituted carbon center.