Main Menu
Predictive Hierarchical Modeling of Chemical Separations and Transformations in Functional Nanoporous Materials: Synergy of Electronic Structure Theory, Molecular Simulation, Machine Learning, and Experiment

Collaborative Network


The Nanoporous Materials Genome Center (NMGC) discovers and explores microporous and mesoporous materials, including metal-organic frameworks (MOFs), zeolites, and porous polymer networks (PPNs). These materials find use as storage and separation media and catalysts in many energy-relevant processes and their next-generation computational design offers a high-payoff opportunity. Towards that end, the NMGC (i) develops state-of-the-art predictive theories (from high-level electronic structure methods to validated molecular mechanics force fields), predictive modeling tools, applets, databases, and web-based repositories, and (ii) employs them to increase the pace of materials discovery and to understand the fundamentals of interactions and mechanisms that govern performance of nanoporous materials.

Research Activities

Ilja Siepmann

Chris Cramer

Laura Gagliardi

Jason Goodpaster

Donald Truhlar

Michael Tsapatsis

Joseph Hupp

Omar Farha

Randy Snurr

Aurora Clark

Michael Deem

David Sholl

Nandini Ananth

Jeffrey Long

Martin Head-Gordon

Berend Smit

Wendy Queen

Maciej Haranczyk

Jeff Neaton