We are a statistical mechanics research group at the University of Minnesota specializing in particle-based computer simulation. Our research efforts are driven by the desire to learn about complex chemical systems on the microscopic, or molecular, level. We focus on understanding how molecular architecture and composition influence structure, phase behavior and function of the system of interest. The challenge of molecular simulation is the ability to make thermodynamic predictions that are both accurate and precise. Accuracy is dependent upon a correct description of molecular interactions in the system, modeled using a force field. Precision is dependent on the degree to which relevant (highly-probable) configurations of the system are sampled. In answering this challenge, our group has developed transferable force fields (TraPPE-UA, TraPPE-EH, TraPPE-pol) that more reasonably model the potential energy of interacting molecules, particularly for the calculation of phase equilibria, and novel simulation algorithms, such as configurational-bias Monte Carlo (CBMC) and aggregation-volume-bias Monte Carlo (AVBMC), for improving the ability to sample important configurations of the system. Our Monte Carlo search algorithms and the Transferable Potentials for Phase Equilibria (TraPPE) force field allow us to predict both accurate and precise thermodynamic data for a wide range of chemical systems, including systems which are not amenable to conventional simulation approaches and for which experimental data are not readily accessible. Please visit our research page to learn more!
September 22, 2016 | Take the Best, Leave the Rest
Integrated computational and experimental research discovers new ways to sort molecules for clean energy and other applications.
News highlight on Department of Energy, Office of Science webpage
Related articles published in:
Nature Communications 6, Article number: 5912 (2015) and Angew. Chem. Int. Ed. 55, 5938 (2016)
September 8, 2016 | Second-year Graduate Student, Jingyi Chen is Honored for 4.0 Grade Point Average
July 25, 2016 | Researchers Develop New Approach for Studying Reaction Equilibria in Complex Chemical Systems
Graduate student Evgenii Fetisov and Professor Ilja Siepmann have developed a new simulation approach to predict reactive equilibria. See ACS Central Science 2, 409 (2016)
April 27, 2016 | Evgenii Fetisov & Mansi Shah Awarded Doctoral Dissertation Fellowships
Congratulations, Evgenii & Mansi!