Heejung Roh

Heejung Roh is a graduate student in mechanical engineering focusing on the design of mixed ionic-electronic semiconductors based on conjugated polymers and conductive metal-organic frameworks. These materials respond electronically to ionic fluxes and vice versa, mimicking synaptic communication to enable biointerfaces and low-energy operation. While they underpin electrochemical devices including batteries, transistors, bioelectronics, and in-memory hardware for neuromorphic computing, how molecular structure translates to device performance remains unresolved. As a MathWorks Fellow, Heejung will develop computational frameworks to quantify how molecular-level design choices propagate to macroscopic device behavior by disentangling ionic and electronic contributions to mixed conduction. She will integrate ion-material interactions, multiscale transport, and machine learning into a unified framework for mapping structure-property-performance relationships. Heejung uses MATLAB for symbolic physics derivation, simulation of decoupled ion-electron conduction, optimization under physicochemical constraints, construction of domain-aware neural networks, and development of generative workflows. This work aims to establish design principles for accelerating the development of electrochemical devices, spanning from energy storage to next-generation ionoelectronics.