Description:

Department of Chemistry Special Seminar

Pratyush Tiwary (University of Maryland)

Title: Inferring phase transitions and critical exponents without having seen any transitions

Abstract: Predicting and characterizing phase transitions is crucial for understanding generic physical phenomena such as crystallization, protein folding and others. However, directly observing phase transitions is not always easy, and often one has limited observations far from the phase boundary and measured under some specific thermodynamic conditions. Here I will discuss new computational methods developed by my group that combine Generative AI with principles of statistical mechanics to develop models that can extrapolate across conditions in temperature, pressure etc at which simulations were never even performed. I will discuss a range of examples possibly including calculating critical exponents for Ising models, protein non-native conformations, crystal polymorphs and RNA tertiary structural ensemble calculation. 

Hosted by Todd Gingrich