Data-driven discovery and substrate scope mapping of dual-ligand nickel catalysts for C(sp2)–C(sp3) cross-electrophile coupling

Dual-ligand nickel catalysis has emerged as an effective strategy for improving C( sp 2 )–C( sp 3 ) cross-electrophile coupling (XEC), yet the systematic studies identifying productive ligand combinations and mapping their target scope remain limited. In this work, we combine high-throughput experimentation (HTE) with a simple, interpretable data-analysis workflow to identify and validate synergistic bidentate–tridentate ligand pairs for Zn-mediated Ni-catalyzed XEC. An HTE screening campaign spanning nine model reactions and 77 ligand combinations per plate enabled simultaneous evaluation of performance, robustness, and non-additive behavior of the catalytic systems. Statistical analysis revealed six ligand pairs that combined strong overall activity with measurable positive synergy, including combinations related to previously reported systems as well as new productive pairings. Using a diverse panel of 96 pharmaceutically relevant (hetero)aryl bromides, we demonstrated that dual-ligand systems often outperformed the best single ligand and could cover the studied substrate space more efficiently. Critically, for certain dual-ligand catalysts, these benefits tracked with interpretable electronic descriptors, providing a practical basis for prioritizing which substrate classes are most likely to profit from the usage of ligand pairs. Together, these results demonstrate that HTE coupled with lightweight statistical analysis provides an efficient route to the discovery of complex catalytic systems, their prioritization and mapping their scope. Our findings also establish dual-ligand Ni catalysis as a practical strategy for expanding the scope and increasing the success rate of thermally driven XEC relevant to pharmaceutical synthesis.