Professor Mark Tuckerman, New York University.  “Exploration and learning of free energy landscapes of molecular crystals and oligopeptides.”  Harvard/MIT/BU Theoretical Chemistry Seminar.Abstract:  Theory, computation, and high-performance computers are playing an increasingly important role in helping us understand, design, and characterize a wide range of functional materials, chemical processes, and biomolecular/biomimetic structures. The synergy of computation and experiment is fueling a powerful approach to address some of the most challenging scientific problems. In this talk, I will describe the efforts we are making in my group to develop new computational methodologies that address specific challenges in free energy exploration and generation. In particular, I will describe our recent development of enhanced free energy based methodologies for predicting structure and polymorphism in molecular crystals and for determining conformational equilibria of oligopeptides. The strategies we are pursuing include heterogeneous multiscale modeling techniques, which allow “landmark” locations (minima and saddles) on a high-dimensional free energy surface to be mapped out, and temperature-accelerated methods, which allow relative free energies of the landmarks to be generated efficiently and reliably. I will then discuss new schemes for using machine learning techniques to represent and perform computations using multidimensional free energy surfaces and navigate chemical compound space in an effort to discover new compounds.