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 phase and adsorption equilibria, self-assembly behavior, and function of the system of interest. The success of molecular simulations hinges on 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 a family of transferable force fields (TraPPE) that more accurately describe the potential energy of interacting molecules, particularly for the calculation of phase and adsorption equilibria, and efficient Monte Carlo simulation algorithms. In addition, our group develops data science approaches that transition simulation data at discrete state points (temperature, pressure, composition) to continuous representations, that reduce the computational load or help to interpret trajectory data for complex systems. Please visit our Publications page to learn about current research projects.