Multi-Scale AI for Molecular Design, Materials Discovery, and Semiconductor Manufacturing by Dr James L. Hedrick
NTU MSE Seminar Hosted by Prof Cho Nam-Joon
Abstract
Automation and machine learning are transforming how we design catalysts, synthesize polymers, and optimize semiconductor manufacturing. We present an integrated framework in which automated flow chemistry generates high-quality datasets for model training; recommender systems and generative AI propose new catalysts and polymer architectures; and multimodal deep-learning models analyze semiconductor etch outcomes by linking PFAS-heavy plasma conditions to nanoscale trench defects. Together, these approaches unify molecular design, materials discovery, and manufacturing optimization, establishing a scalable AI pipeline from chemistry to devices and pointing toward future integration of quantum optimization methods.
Biography
James L. Hedrick
IBM Research Silicon Valley Lab, San Jose, CA
James L. Hedrick is a Distinguished Research Staff Member at IBM’s Almaden Research Center, where he currently focuses his efforts in AI-assisted catalyst discovery for polymer synthesis. He is also a Visiting Scholar at Stanford University and maintains a long-standing affiliation with the Institute of Bioengineering and Nanotechnology (IBN) in Singapore.
Over the course of his career, Jim has pioneered novel polymer-forming reactions, including the development of high-temperature interlayer dielectrics and block copolymers for low dielectric materials—foundational to block copolymer lithography. He introduced the polymer community to organic catalysis as an environmentally benign route to living polymerization, opening new avenues in nanomedicine, degradable polymers, and polymer recycling.
These advances have fueled translational research addressing critical challenges such as antimicrobial resistance, gene delivery, sustained therapeutic release, and cancer therapies. His work has led to multiple spin-off companies focused on polymer recycling and nanoscale lithographic patterning.
Jim is the author of over 570 publications and holds approximately 545 patents. He serves on numerous scientific advisory boards and has received many prestigious honors, including:
- Member, National Academy of Engineering (2014)
- ACS Award in Cooperative Chemistry with IBN Singapore (2025)
- IBM Grand Challenge Award on Antibiotic Resistance (2017)
- ACS Herman Mark Senior Scholar Award (2017)
- President Obama’s EPA Green Chemistry Award (2012)
- ACS Polymer Fellow (2010)
- ACS Carl Marvel Award for Creative Polymer Chemistry (2003)
- ACS Award in Cooperative Chemistry with Stanford University (2009)
- IBM Master Inventor (2018)
Currently, Jim is engaged in a diverse, multidisciplinary effort to accelerate the discovery of sustainable and high-performance materials using artificial intelligence.