Predicting the stability of base-mediated C–H carboxylation adducts using data science tools

Base-mediated C–H carboxylation is a versatile pathway for utilizing carbon dioxide (CO2) as a C1 building block in organic synthesis. However, CO2 constitutes a notorious thermodynamic sink, which restricts this approach to activated or intrinsically reactive nucleophiles. To qualitatively assess the stability of CO2 adducts, we present a computational approach that integrates quantum chemistry with statistical modeling to build a predictive workflow. The target property is the CO2 affinity, specifically the negative Gibbs free reaction energy. This predictive workflow has been applied to 60 novel carbon-centered nucleophiles, suggesting reactions that yield stable carboxylation adducts. The results have been validated through experimental methods for five predicted nucleophiles, which include three stable and two unstable adducts.