Today 2026 March15 (Sun) 11:54 Etc/GMT-9

2026/04/15 00:30~2026/04/15 01:30

ChE ExxonMobil Lecture: Ed Maginn, Notre Dame, "Keeping it Cool: Leveraging Molecular Simulation and Data-Driven Methods for Next-Generation Refrigeration"

Sponsoredby the Department of Chemical and Biomolecular EngineeringHosts: Peng Bai and Clark Chenpengbai@umass.edu and zhuchen@umass.edu413-545-6189 and 413-545-6145 Edward Maginn University of Notre Dame “Keeping itCool: Leveraging Molecular Simulation and Data-Driven Methods forNext-Generation Refrigeration” Tuesday, April 14, 2026, 11:30 a.m.201 LGRT, UMass Amherst(Refreshmentsat 11:15 a.m.) Abstract:Most refrigerants used today arehydrofluorocarbons (HFCs), potent greenhouse gases with global-warmingpotentials 2000–4000 times that of CO2. Their environmental impactis compounded by high leak rates—nearly 90% of refrigerants eventually escapeinto the atmosphere—and the massive energy demand of HVACR systems, whichaccount for up to 40% of U.S. building electricity usage. Consequently, theU.S. and international partners are phasing down HFCs under agreements like theKigali Amendment and the AIM Act. This creates a tremendous societal challengeto responsibly replace billions of kilograms of incumbent refrigerants. The NSFERC project EARTH was formed to address this by developing strategies for bothrepurposing existing refrigerants and discovering sustainable alternatives. In this talk, I will discuss our effortsto address this challenge by integrating molecular simulations with machinelearning methods. We have used data science methods to develop highly accurateintermolecular potentials for a wide class of HFCs, enabling the prediction ofessential thermophysical properties for refrigerants and their complexmixtures. We leverage these tools to discover new solvents capable ofseparating azeotropic mixtures of existing HFCs, a key step for recycling. Weuse active learning to minimize both computational cost and experimental time.Finally, moving beyond existing fluids, we have combined group contributionapproaches with Gaussian process regression to develop rapid screening methodsfor millions of potential replacements for high-GWP HFCs. These approachesdemonstrate how integrating machine learning with fundamental physics-basedsimulations leads to faster property predictions and new design principles forsustainable materials.    Bio: Edward Maginn is the Keough-Hesburgh Professor in theDepartment of Chemical and Biomolecular Engineering at the University of NotreDame. He also serves as Notre Dame’s Associate Vice President of Research. Hisresearch group develops and applies advanced molecular simulation methods tostudy the structure and thermophysical properties of fluids. Maginn was a pioneer in the use ofmolecular simulations to investigate ionic liquids and holds nine patents inthe field. He has over 270 peer-reviewed publications and has written 10 bookchapters. He is a Fellow of the American Institute of Chemical Engineers, theAmerican Association for the Advancement of Science, and the National Academyof Inventors. He is a Trustee and Executive Director of the non-profit CACHECorporation, which promotes the use of computational methods in chemicalengineering. He has BS in chemical engineering fromIowa State University and a PhD in chemical engineering from the University ofCalifornia, Berkeley. He worked for Procter and Gamble from 1987-1990 and hasbeen on the Notre Dame faculty since 1995.  

📍 LGRT 201