IBM-Illinois Discovery Accelerator Institute Seminar
Prof. Rafael Gómez-Bombarelli
Massachusetts Institute of Technology
Thursday, March 21st, 2024
10:00 am CST, Coordinated Science Laboratory Room 1232
“Computational materials design with machine learning and atomistic simulations”
Abstract: Designing new materials is vital to address pressing challenges in health, energy, and sustainability. The computational techniques of atomistic simulation and machine learning (ML) offer an avenue to rapidly invent new materials and navigate this enormous space. By populating the continuum between physics-based simulations and machine learning, the Learning Matter Lab seeks to enable rapid, computation-first design of materials that accelerate the materials discovery cycle.
ML enables a new paradigm: surrogate models fuse simulations with experimental data at a fraction of the cost, while embedding physics-based priors to ensure robustness and transferability. The speed and accuracy of these models allows inverse design of materials for many applications. We will present our progress in enabling experimentally validated materials design for multiple materials classes and applications, such as heterogeneous nanoporous thermo-catalysts (zeolites); composition and surface engineering of perovskite oxide electrocatalysts, organic and inorganic solid electrolytes for batteries, therapeutic peptides, recyclable thermoset plastics, carbon-capture nucleophiles to replace amines, stable and optically tuned organic electronics for OLED and OPV.
Biography: Professor Gómez-Bombarelli received his BS, MS, and PhD in chemistry from the University of Salamanca in Spain, followed by postdoctoral work at Heriot-Watt University in Scotland. As a postdoc at the Aspuru-Guzik lab at Harvard University he worked on high-throughput virtual screening for organic light-emitting diode (OLED) and battery electrolytes. He entered industry in 2016 as a senior researcher at Japanese technology company Kyulux, applying Harvard-licensed technology to build commercial OLED products. He joined the DMSE faculty in 2018. Professor Gómez-Bombarelli’s work has been featured in publications such as MIT Technology Review and the Wall Street Journal. He is co-founder of Calculario, a materials discovery company that uses quantum chemistry and machine learning to target advanced materials in high-value markets