AI-MI Seminar Series: Recovering Molecular Heterogeneity using Molecular Simulation, Electron Microscopy, and Machine Learning

Join us and explore how researchers are combining molecular simulation, machine learning, and electron microscopy to better understand structural heterogeneity in complex chemical systems. The talk will highlight new algorithms that integrate computational models with experimental imaging to uncover hidden states in biomolecules and materials—helping bridge the gap between design and function at the nanoscale.

Watch live at youtube.com/@AIMaterialsInstitute

Topic: Many of the chemical systems most relevant to modern science and technology — proteins, doped semiconductors, and catalysts – are structurally heterogeneous at scales of nanometers or smaller. Understanding this heterogeneity is crucial to understanding the link between their design and their function. Molecular simulation and machine learning tools have the ability to visualize this heterogeneity with incredible specificity, but are inherently limited by model biases. Experimental techniques, such as electron microscopy, have the opposite approache – they can image heterogeneity in real samples, but must contend with low signal-to-noise ratio and ambiguity in the imaging process. Consequently, there is a need for new data assimilation approaches that directly combine these techniques. In this talk, I review our recent progress towards developing new algorithms that integrate computational tools with electron microscopy data. We initially focus on biomolecular electron microscopy, where we introduce algorithms that integrate electron microscopy with molecular dynamics, as well as structure prediction tools such as Alphafold3-like models. On test systems, our algorithms are able to recover states that are missing from the model, improving heterogeneous prediction. We then discuss our initial work transferring these ideas to electron microscopy of materials.

Speaker: Erik Thiede is an Assistant Professor of Chemistry at Cornell University. He received his PhD from the University of Chicago working with Profs. Aaron Dinner and Jonathan Weare. He then did a postdoc at the Flatiron Institute CCM, working with Prof. Risi Kondor, Dr. Pilar Cossio, and Dr. Sonya Hanson. Erik’s research area is theoretical and computational chemistry.