Rapid and Mild One‐Flow Synthetic Approach to Unsymmetrical Sulfamides Guided by Bayesian Optimization

Bayesian optimization (BO) is regarded as an efficient approach that can identify optimal conditions using a restricted number of experiments. Despite demonstrated potential BO, applications BO-based approaches in synthetic organic chemistry remain limited. Herein, we achieved the first rapid and mild (5.1 s, 20 °C) one-flow synthesis unsymmetrical sulfamides from inexpensive sulfuryl chloride. Undesired reactions were successfully suppressed risk handling chloride was minimized by use micro-flow technology. The reaction producing ≥75 % yield identified machine learning based on BO. It BO produced desired with small experiments (19 10 experiments) entire search space (10,500 combinations conditions). Gaussian process (GP) models provided relationships between parameters outputs (RCRPO).