In silico Design of Porous Polymer Networks: High-Throughput Screening for Methane Storage Materials
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Porous polymer networks (PPNs) are a class of advanced porous materials that combine the advantages of cheap and stable polymers with the high surface areas and tunable chemistry of metal-organic frameworks. They are of particular interest for gas separation or storage applications, for instance, as methane adsorbents for a vehicular natural gas tank or other portable applications. PPNs are self-assembled from distinct building units; here, we utilize commercially available chemical fragments and two experimentally known synthetic routes to design in silico a large database of synthetically realistic PPN materials. All structures from our database of 18,000 materials have been relaxed with semiempirical electronic structure methods and characterized with Grand-canonical Monte Carlo simulations for methane uptake and deliverable (working) capacity. A number of novel structure-property relationships that govern methane storage performance were identified. The relationships are translated into experimental guidelines to realize the ideal PPN structure. We found that cooperative methane-methane attractions were present in all of the best-performing materials, highlighting the importance of guest interaction in the design of optimal materials for methane storage.
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Demonstrations have included the screening of the more than 13k MOFs in the ToBaCCo set for hydrogen storage or other similarly large MOF sets for methane storage.
“Demonstrations have included the screening of the more than 13k MOFs in the ToBaCCo set (28) for hydrogen storage (47) or other similarly large MOF sets for methane storage (39, 48).”
From Machine Learning for the Discovery, Design, and Engineering of Materials. (2022) · cites this paper as [48]
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- Authors
- Martin, R. L., Simon, C. M., Smit, B., & Haranczyk, M.
- Affiliations
- Lawrence Berkeley National Laboratory (US)
- University of California, Berkeley (US)
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
- Venue
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-03-24
- Volume
- 136
- Issue
- 13
- Pages
- 5006-5022
- ISSN
- 0002-7863 (ISSN-L)
- 1520-5126
- OpenAlex
- W2009317314
- Cited by
- 170
- References
- 55
- Citations by year
- 2026: 5 · 2025: 11 · 2024: 9 · 2023: 9 · 2022: 12 · 2021: 14 · 2020: 22 · 2019: 22 · 2018: 16 · 2017: 9 · 2016: 17 · 2015: 18 · 2014: 5
- FWCI
- 6.95
- Type
- journal article
- Language
- en
- Open access
- green
- infoscience.epfl.ch
- Licence
- cc-by-nc-nd
- Locations
- Journal of the American Chemical Society (publishedVersion)
- PubMed (publishedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- Funders
- Advanced Research Projects Agency - Energy (DE-AR0000249)
- Topics
- Physical Sciences › Chemistry › Inorganic Chemistry › Metal-Organic Frameworks: Synthesis and Applications
- Physical Sciences › Materials Science › Materials Chemistry › Covalent Organic Framework Applications
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Keywords
- porous polymer networks, methane storage, methane adsorption, high-throughput screening, structure-property relationships, gas storage materials, grand canonical Monte Carlo simulation, self-assembled polymers
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