Unravel key factors in α,β-unsaturated carboxylic acid salts one-pot synthesis from CO2 and alkenes: parameterization of bidentate ligands in transition-metal complexes

Abstract

Transition metal-catalyzed CO<inf>2</inf> conversion to value-added chemicals faces the challenge of balancing selectivity and activity. Here, we integrate multivariate linear regression (MLR) with density functional theory (DFT) to establish a predictive framework to optimize catalytic systems for CO<inf>2</inf>/C<inf>2</inf>H<inf>4</inf> coupling. The classical steric descriptors percent buried volume (%V<inf>bur</inf>) and bite angle were shown to be non-equivalent, and their interplay is explained by an “interaction term transformation strategy”. By rationally tuning the electronic, steric and geometric properties of the catalyst, we design a high performance PPh<inf>2</inf>-ImPy-Ni(0) catalyst for CO<inf>2</inf>/C<inf>2</inf>H<inf>4</inf> coupling, achieving a record TON of 570 with 82 % yield. A novel buried volume of octants (V<inf>BO</inf>) descriptor is proposed that can be extended to identify thresholds separating high-active/low-active regions in the CO<inf>2</inf>/alkene coupling, analogous to previous ligand classification systems. Most importantly, our stepwise energy decomposition approach – from DFT-computed Gibbs free energy (ΔG) to electronic energy (ΔE), interaction energy (ΔE<inf>int</inf>), and ultimately to the PIO-based bond index (PBI) – provides a generalizable framework for mechanistically interpreting reaction reactivity. These studies illuminate the broad applicability of hypotheses concerning the structural impact of various classes of bidentate ligands on reaction mechanisms, offering a robust methodology likely to be instrumental in advancing future ligand research. © 2025