Organization profile
Organization profile
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 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 develops state-of-the-art predictive modeling tools and employs them to increase the pace of materials discovery. The NMGC provides a repository of experimental and predicted structures and associated properties for the rapidly growing scientific communities that are interested in using these materials in energy-relevant technologies.
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. Our work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being -
SDG 6 Clean Water and Sanitation -
SDG 7 Affordable and Clean Energy -
SDG 8 Decent Work and Economic Growth -
SDG 9 Industry, Innovation, and Infrastructure -
SDG 12 Responsible Consumption and Production -
SDG 13 Climate Action
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Collaborations and top research areas from the last five years
Profiles
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Melanie F Burns
- Advanced Technologies for Preservation of Biological Systems (ATP-BIO)
- Nanoporous Materials Genome Center - Managing Director
- Inorganometallic Catalyst Design Center - Managing Director
Person: Executive, Administrative, and Managerial Staff
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Projects
- 2 Finished
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NMGC: Nanoporous Materials Genome: Methods and Software to Optimize Gas Storage, Separations, and Catalysis (Phase 2)
Siepmann, I. (PI), Cramer, C. (CoI), Gagliardi, L. (CoI), Truhlar, D. G. (CoI), Tsapatsis, M. (CoI) & Goodpaster, J. D. (CoI)
U.S. DEPARTMENT OF ENERGY (USDOE)
9/1/17 → 8/31/21
Project: Research project
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NMGC: Nanoporous Materials Genome: Methods and Software to Optimize Gas Storage, Separations, and Catalysis (Phase 1)
Siepmann, I. (PI), Cramer, C. (CoI), Gagliardi, L. (CoI), Truhlar, D. G. (CoI), Tsapatsis, M. (CoI) & Goodpaster, J. D. (CoI)
9/1/12 → 8/31/17
Project: Research project
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Discovery of Stacking Heterogeneity, Layer Buckling, and Residual Water in COF-999-NH2 and Implications on CO2Capture
Daglar, H., Zhou, Z., Zhu, R., Parihar, P., Siepmann, J. I., Yaghi, O. M. & Gagliardi, L., Jan 14 2026, In: Journal of the American Chemical Society. 148, 1, p. 1614-1622 9 p.Research output: Contribution to journal › Article › peer-review
1 Link opens in a new tab Scopus citations -
Solvent-Inclusive ML/MM Simulations: Assessments of Structural, Dynamical, and Thermodynamic Accuracy
Gopal, V., Kirkvold, C., Gordon, A., Goodpaster, J. D. & Sarupria, S., Jan 12 2026, In: Journal of Chemical Information and Modeling. 66, 1, p. 110-121 12 p.Research output: Contribution to journal › Article › peer-review
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A hybrid meta on-top functional for multiconfiguration pair-density functional theory
Bao, J. J., Zhang, D., Zhang, S., Gagliardi, L. & Truhlar, D. G., Jan 7 2025, In: Proceedings of the National Academy of Sciences of the United States of America. 122, 1, e2419413121.Research output: Contribution to journal › Article › peer-review
Open Access9 Link opens in a new tab Scopus citations
Datasets
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Huzinaga Projection Embedding for Efficient and Accurate Energies of Systems with Localized Spin-densities
Graham, D. S., Wen, X., Chulhai, D. & Goodpaster, J. D., Data Repository for the University of Minnesota, May 7 2021
https://hdl.handle.net/11299/219605
Dataset
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Data for "Ground State Absolutely Localized WF-in-DFT Embedding Energies"
Graham, D. S., Wen, X., Chulhai, D. & Goodpaster, J. D., Data Repository for the University of Minnesota, 2019
DOI: 10.13020/r7c0-2x97, http://hdl.handle.net/11299/208808
Dataset
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Supporting Data for "From Order to Disorder: Computational Design of Triblock Amphiphiles with 1 nm Domains"
Shen, Z., Chen, J., Vernadskaia, V., Ertem, S. P., Mahanthappa, M., Hillmyer, M. A., Reineke, T. M., Lodge, T. P. & Siepmann, I., Data Repository for the University of Minnesota, May 11 2020
DOI: 10.13020/7zcr-w347, https://hdl.handle.net/11299/214077 and one more link, http://hdl.handle.net/11299/214077 (show fewer)
Dataset