Ligand Control of Chain Walking and Regioselectivity in Nickel Catalysis

Title: Ligand Control of Chain Walking and Regioselectivity in Nickel Catalysis

Speaker: A/Prof Sajid Imran, CUHK-Shenzhen

Abstract: The selective formation of C–C bonds at remote, unactivated C(sp³)–H sites remains a major challenge in organic synthesis. Chain-walking catalysis provides a strategy for accessing these sites by combining metal migration along a hydrocarbon chain with subsequent coupling. Achieving predictable regioselectivity through ligand variation alone therefore requires control over the competition between migration and productive coupling. In this seminar, I will present our development of nickel-catalyzed hydroheteroarylation of alkenes with heteroarenes under N-heterocyclic carbene (NHC) ligand control. With aryl-substituted terminal alkenes, ligand choice enables a switch between linear and branched C2-alkyl-substituted heteroarenes by suppressing or promoting chain walking. We subsequently extended tandem migration and coupling to unactivated internal alkenes, including mixtures of alkene isomers, to access linear C2-alkyl-substituted heteroarenes selectively.  Furthermore, we combined experimental investigations with density functional theory calculations to elucidate how NHC ligands control chain walking. Together, these studies provide a mechanistic basis for ligand selection and catalyst design in regioselective tandem chainwalking alkene functionalization.

Bio: Dr Sajid Imran received his PhD in organic chemistry from Soochow University in 2023, where his research focused on N-heterocyclic carbene-supported nickel catalysts for ligand-controlled chain walking and regioselective hydroheteroarylation. During his postdoctoral research at The Chinese University of Hong Kong, Shenzhen, he applied density functional theory and machine learning to investigate aromaticity in ground and excited states, molecular stability, and structure and bonding in boron–nitrogen heterocycles. He is now a Research Assistant Professor in the School of Science and Engineering at CUHK-Shenzhen. His current research integrates experimental and computational approaches with machine learning to investigate main-group-mediated dinitrogen activation for ammonia formation.