Materials Science Research Lecture

***Refreshments at 10:45am in Noyes lobby

Abstract:

Chemical reactions in condensed phases underpin critical processes, from polymerization and carbon-fiber manufacturing to the performance of propellants and explosives. Predictive modeling of these reactions demands seamless integration of detailed chemical kinetics (often under extreme conditions) with the physics of condensed matter, including molecular strain, strain relaxation, and microstructural evolution. The talk highlights a unified computational strategy that connects quantum chemistry, materials physics, and machine learning to tackle long-standing challenges across applications.

This presentation begins by examining nuclear quantum effects (NQEs) on the multistep reaction pathways of a molecular crystal. I will contrast the quantum behavior observed in these systems with simplified approaches for incorporating NQEs into classical molecular dynamics (MD) simulations. Next, I will demonstrate how local molecular strain dramatically modulates reaction energetics in both polymers and molecular crystals, and how machine-learning models can learn these effects. We map the local structure to strain-energy landscape to predict reaction barriers on the fly. Using these models, we have computed activation energies for the key reactions governing carbon-fiber processing, yielding atomistic structural models of these materials with unprecedented fidelity.

Finally, I will show how AI-driven analysis of large-scale MD simulations extracts quantitative microstructural effects, which are then embedded as sub-grid-scale physics in finite-element models. This multiscale framework delivers predictive simulations of the shock-to-detonation transition in complex energetic materials—bridging atomic-scale chemistry to macroscopic performance.

More about the Speaker:

Alejandro Strachan is the Reilly Professor of Materials Engineering at Purdue University, the Co-Director of nanoHUB, and Purdue's Office of Research Fellow for Intelligent Twins and Digital Innovation. Before joining Purdue, he was a Staff Member in the Theoretical Division of Los Alamos National Laboratory and worked as a Postdoctoral Scholar and Scientist at Caltech. He received a Ph.D. in Physics from the University of Buenos Aires, Argentina. Prof. Strachan's research focuses on predictive atomistic and multiscale models grounded on first principles to advance our ability to understand, design, and deploy materials. His recent work integrates machine learning and artificial intelligence with physics-based modeling to tackle critical scientific and engineering challenges in areas such as energy, electronics, and manufacturing. In addition, Strachan's scholarly work includes cyberinfrastructure to make simulations, models, and data widely accessible and useful in research and education to accelerate innovation. nanoHUB has served over 200,000 simulation users and reached 800+ US institutions of higher education. Prof. Strachan has published over 200 peer-reviewed scientific papers and his contributions to research and education have been recognized by several awards, including the Early Career Faculty Fellow Award from TMS in 2009, an R&D 100 award in the category of software and services for nanoHUB (2020), and the Reilly Chair Professorship in 2023.