Data-driven recommendation of agents, temperature, and equivalence ratios for organic synthesis

A machine learning framework predicts suitable agents, temperature, and equivalence ratios for reactants and agents. The model consistently outperforms strong baselines, enabling more complete and automation-ready reaction protocols.