Topology, Molecular Simulation, and Machine Learning as Routes to Exploring Structure and Phase Behavior in Molecular and Atomic Crystals
- TH Department Online Seminar
- Date: Jan 14, 2021
- Time: 04:30 PM - 06:00 PM (Local Time Germany)
- Speaker: Prof. Dr. Mark E. Tuckerman
- Professor of Chemistry and Mathematics, Department of Chemistry, New York University, USA
- Room: Join zoom meeting: https://tum-conf.zoom.us/j/69317054390 | Meeting ID: 693 1705 4390 | Passcode: 788618
Crystallization conditions can influence polymorph selection, making an experimentally driven hunt for polymorphs difficult. Such efforts are further complicated when polymorphs initially obtained under a particular experimental protocol “disappear” in favor of another polymorph in subsequent repetitions of the experiment. Consequently, theory and computation can potentially play a vital role in mapping the landscape of crystal polymorphism. Traditional crystal structure prediction methods face their own challenges, and therefore, new approaches are needed. In this talk, I will show, by leveraging concepts from mathematics, specifically geometry and topology, and statistical mechanics in combination with techniques of molecular simulation, traditional methods, and machine learning, that a new paradigm in crystal structure prediction may be emerging. Examples demonstrating prediction of structures of crystals, co-crystals, and phase transitions will be presented.