Leaps-MPS: memory-based simulation approaches: developing computational methods and scientists

Funding Agency & Program: National Science Foundation (NSF), Division of Chemistry, Mathematical and Physical Sciences (CFDA 47.049) and LEAPS-MPS (Launching Early-Career Academic Pathways) Program

Award Details: Chatham University, under the direction of Professor William C. Pfalzgraff, received $249,950 in project grant funding (Award Date: September 15, 2025; Completion Date: August 31, 2027) to develop computational methods that accelerate the calculation of molecular properties from computer simulations. The project focuses on creating formally exact generalized master equation (GME) approaches that extract correlation functions efficiently from molecular dynamics simulations, enabling faster and more accurate calculations of transport properties and spectra in complex condensed-phase systems. These computational advances are applicable to research areas including drug design, advanced materials, and energy production.

Educational and Research Outcomes: Beyond core methodological development, this award supports comprehensive workforce development by establishing structured pathways for training undergraduate students in theoretical chemistry research. The initiative integrates early research exposure, programming and mathematics instruction, multi-level mentoring, and open-source code development to cultivate the next generation of computational chemistry scientists. The work leverages memory kernels to maximize information extraction from limited simulation data, addressing a fundamental limitation that has historically constrained researchers' ability to study complex systems of interest.

Abstract

In this project, funded by the MPS-leaps (launching early-career academic pathways) program and the chemical structure and dynamics (CSD) program in the division of chemistry, professor william c. Pfalzgraff and his students at chatham university will develop computational methods to accelerate the calculation of molecular properties from computer simulations. Computer simulations of molecules and materials are essential tools in modern chemistry, but calculating properties like viscosity, diffusion rates, and spectra from these simulations can require significant computational time and resources. The challenge associated with obtaining accurate correlation functions that can provide physical insight and allow the calculation of transport coefficients and spectra from simulations often limits researchers' ability to study complex systems of interest. Professor pfalzgraff and his students will develop formally exact generalized master equation (GME) approaches that can be applied to any system to calculate correlation functions accurately and efficiently from molecular dynamics simulations. Their studies could open the door to more efficient calculations of transport properties and spectra in a wide variety of complex condensed phase systems relevant to drug design, advanced materials, and energy production. This work will also create comprehensive pathways for training undergraduate students in theoretical chemistry research using early research exposure, integrating training in programming and mathematics with research, multi-level mentoring, and open-source code development. This work seeks to develop methods that extract maximum information from limited simulation data by using memory kernels that encode how the environment influences the dynamics of observable of interest. In many condensed phase systems, these memory kernels decay to zero more rapidly than the correlation functions themselves, allowing researchers to run short simulations to obtain the memory kernel and then use the GME to predict long-time behavior with minimal additional computational cost. The research team will optimize collocation-based numerical methods for extracting memory kernels from simulation data and explore alternative mathematical formulations that accelerate memory kernel decay. The methods will be implemented in open-source software that can be applied to any molecular system. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are not planned for this award.