ChE Seminar: Stephen Lam, University of Massachusetts, Lowell,“AI-Guided Chemical Science for Advanced Nuclear Energy Systems: Chemistry, Structure, and Properties Across the Periodic Table”

ChE Seminar: Stephen Lam, University of Massachusetts, Lowell,“AI-Guided Chemical Science for Advanced Nuclear Energy Systems: Chemistry, Structure, and Properties Across the Periodic Table”

Host: Dimitrios Maroudas and Zhu ChenSponsored by the Department of Chemical and Biomolecular Engineering  Stephen Lam University of Massachusetts Lowell “AI-Guided ChemicalScience for Advanced Nuclear Energy Systems: Chemistry, Structure, andProperties Across the Periodic Table” Tuesday, February 10, 2026, 11:30 a.m.201 LGRT, UMass Amherst(Refreshments at 11:15 a.m.) Abstract:A central challenge to deployingadvanced nuclear technologies lies in our ability to accurately characterize,predict, and monitor the chemistry of materials throughout the operational lifeof reactor and fuel cycle. In fission and fusion environments, nucleartransmutation results in a vast array chemical products that are formed underextreme conditions including high temperatures, pressures, and radiationfields. Here, current experimental and computational approaches are eitherinsufficiently accurate or expeditious for assessing these design spaces. Assuch, it is unlikely that we will achieve the robust chemical understandingrequired for commercial deployment of advanced nuclear energy systems usingconventional research paradigms. This talk will discuss our latest advances inapplying artificial intelligence (AI) to overcome these challenges for studyingthe chemistry-structure-property relationships in molten salt, which include 1)machine learning (ML)-assisted atomistic simulation for speed and accuracy, 2)chemistry-informed ML for learning the thermal properties of molten saltsacross the periodic table and generative AI for targeted-property design, and3) machine learning-enhanced characterization and online monitoring withspectroscopic methods. We will show how state-of-the-art methods have beenapplied for uncovering structure-property of molten salts with unprecedentedspeed and resolution and discuss future opportunities for improvement in eachof these areas. Bio:Stephen Lam is the Director of Nuclear Engineering, andAssistant Professor of Chemical Engineering at the University of MassachusettsLowell. His research focuses on integrating artificial intelligence andmaterials simulation with experimental characterization techniques for thepurpose of understanding chemical structure, reactions and propertyrelationships in advanced energy materials. Stephen obtained a PhD in NuclearScience and Engineering in 2020 from the MIT, and BS in Chemical Engineering in2013 from the University of British Columbia. He was the recipient of the U.S.Department of Energy Early Career Award, and U.S. Nuclear RegulatoryCommission’s Distinguished Faculty Advancement Award in 2024. His work has beenpublished in over 30 peer-reviewed articles (including JACS Au, Nature MachineIntelligence, npj Computational Materials, Chemical Science) in areas ofmachine learning, molten salt chemistry, tritium interactions with materials,carbon materials, and high-temperature ceramics.

📍 LGRT 201

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