Heecheol Jang

Heecheol Jang is a graduate student in chemical engineering developing computational models to quantify the force-responsiveness of mechanophores, molecules whose mechanically labile bonds cleave under lower force than typical covalent bonds. Discovering novel mechanophores could enable next-generation polymers with enhanced toughness and self-healing properties, yet the underlying principles remain poorly understood. He develops a generalized tensioned model for bond activation using force-free reaction descriptors and effective spring constants to predict experimentally measured force responsiveness with significantly lower computational cost than direct force simulations. Heecheol extends this framework beyond carbon-carbon bond cleavage to organic mechanophores with non-CC bonds, incorporating electrostatic and steric descriptors, and develops a machine learning framework for high-throughput discovery of transition metal complex mechanophores. To generate machine learning descriptors, he converts discrete density functional theory outputs into continuous representations. As a MathWorks Fellow, Heecheol will expand the discovery framework and conduct benchmark calculations, establishing foundations for the de novo design of novel polymers with enhanced toughness and self-healing capabilities.