predictive hierarchical modeling of chemical separations and transformations in functional nanoporous materials: synergy of electronic structure theory, molecular simulation, machine learning, and experiment
April 12, 2022 | Research.com, a prominent academic platform for scientists, has just published the 2022 edition of their Ranking of Top Scientists. Fourteen current and past NMGC senior investigators were included in the rankings in the disciplines of Chemistry and Materials Science.
April 8, 2022 | Former undergraduate student Nico Mendez (Colina Group, University of Florida) was awarded a fellowship in the 2022 National Science Foundation Graduate Research Fellowship Program (GRFP). During his time in NMGC, Mendez studied the adsorption of gases in polymers of intrinsic microporosity using monte carlo and molecular dynamics simulation techniques. He co-authored 2 NMGC publications, one as a co-first author. Mendez is currently a graduate student at Columbia University, in the Sanat Kumar group, where he is working on the crystallization kinetics and dispersion of semicrystalline polymers.
April 8, 2022 | The 2022 All-Hands Meeting was held on April 4-5. Members joined in person at the McNamara Alumni Center on the University of Minnesota campus and online via Zoom to discuss current and future research.
April 28, 2021 | Yangzhesheng (Andrew) Sun (Siepmann Group) has been awarded a Dissertation Fellowship.
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The article “Ethanol and Water Adsorption in Conventional and Hierarchical All-Silica MFI Zeolites” is featured on the March 2022 cover of the ACS Physical Chemistry Au. The cover, designed by Lisa Zeeb, shows the selective adsorption and preferential siting for liquid-phase adsorption of ethanol/water mixtures (low and intermediate concentrations are shown from left to right) in a hierarchical all-silica MFI.
The work of NMGC researchers in the groups of Coray Colina (University of Florida) and David Sholl (Georgia Tech), which appeared in Nature Publishing Journal Computational Materials, provides an extensive dataset of over 240,000 structural conformations of amorphous polymeric materials, adsorption isotherms that account for polymer flexibility, and binary selectivities of 4,140 polymer-mixture combinations, with almost all of them unavailable from experimental works.
The groups of NMGC researchers Randall Snurr (Northwestern University), Laura Gagliardi (University of Chicago), and Alán Aspuru-Guzik (University of Toronto) introduce the Quantum MOF (QMOF) database, a publicly available database of computed quantum-chemical properties for more than 14,000 experimentally synthesized MOFs. In a recent study, the authors demonstrate how machine learning models trained on the QMOF database can be used to rapidly discover MOFs with targeted electronic structure properties, using the prediction of theoretically computed band gaps as a representative example.
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