Mapping Free Energy Landscapes
Modern computer simulations involve tracking the behavior of thousands to millions of atoms. At the core of molecular simulations are two fundamental techniques, Monte Carlo (which performs a random walk to obtain statistics on configurations of a system), and Molecular Dynamics (which integrates Newton's equations directly). Each method relies on efficient computation of inter-molecular pair, intra-molecular bonded and background field interactions. Despite this, important thermodynamic properties such as free energy minima and the reactive pathways between them, require prohibitively expensive calculations. Computational scientists therefore make use of a variety of sampling techniques to efficiently obtain thermodynamic properties. These fall into two primary categories: methods which obtain free energy landscapes, and methods focused on obtaining transition pathways and reactive trajectories.
The Whitmer group has extensive experience in the development, use, and implementation of advanced sampling algorithms and free energy measurements. The group develops and maintains the SSAGES package (Software Suite for Advanced Generalized Ensemble Simulations), which provides a framework for free energy and reactive path sampling that can extend publically available MD codes such as LAMMPS, GROMACS and OpenMD. We are also involved in the development of new free energy sampling methods and simulation techniques. In particular, we wish to use these techniques to understand self-assembly and response of soft materials.