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Progress toward the computational discovery of new metal–organic framework adsorbents for energy applications

Nature Energy volume 9, pages 121–133 (2024)Cite this article

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Abstract

Metal–organic frameworks (MOFs) are a class of nanoporous material precisely synthesized from molecular building blocks. MOFs could have a critical role in many energy technologies, including carbon capture, separations and storage of energy carriers. Molecular simulations can improve our molecular-level understanding of adsorption in MOFs, and it is now possible to use realistic models for these complicated materials and predict their adsorption properties in quantitative agreement with experiments. Here we review the predictive design and discovery of MOF adsorbents for the separation and storage of energy-relevant molecules, with a view to understanding whether we can reliably discover novel MOFs computationally prior to laboratory synthesis and characterization. We highlight in silico approaches that have discovered new adsorbents that were subsequently confirmed by experiments, and we discuss the roles of high-throughput computational screening and machine learning. We conclude that these tools are already accelerating the discovery of new applications for existing MOFs, and there are now several examples of new MOFs discovered by computational modelling.

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Fig. 1: A timeline of some MOFs discovered by computational modelling before synthesis and laboratory testing.
Fig. 2: Examples of MOFs inspired by computational modelling.
Fig. 3: Databases of hypothetical MOFs for high-throughput gas-adsorption simulations.
Fig. 4: Computational discovery of MOFs for gas storage and separation via high-throughput screening.
Fig. 5: A machine learning workflow for adsorption properties in MOFs.

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Acknowledgements

P.Z.M. acknowledges support from the Department of Science, Innovation and Technology (DSIT) and the Royal Academy of Engineering under the Industrial Fellowships programme (IF2223–110). Y.G.C. acknowledges support from the National Research Foundation of Korea (NRF) from grants funded by the Korea government (MSIT; nos. 2020R1C1C1010373 and 2021M3D3A1A01022104). R.Q.S. acknowledges support from the US Department of Energy (DE-FG02-08ER15967).

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Author notes

  1. These authors contributed equally: Peyman Z. Moghadam, Yongchul G. Chung.

Authors and Affiliations

  1. Department of Chemical Engineering, University College London, London, UK

    Peyman Z. Moghadam

  2. School of Chemical Engineering, Pusan National University, Busan, South Korea

    Yongchul G. Chung

  3. Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA

    Randall Q. Snurr

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  1. Peyman Z. Moghadam
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Correspondence to Randall Q. Snurr.

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R.Q.S. has a financial interest in the startup company NuMat Technologies, which is commercializing MOFs. P.Z.M. and Y.G.C. declare no competing interests.

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Moghadam, P.Z., Chung, Y.G. & Snurr, R.Q. Progress toward the computational discovery of new metal–organic framework adsorbents for energy applications. Nat Energy 9, 121–133 (2024). https://doi.org/10.1038/s41560-023-01417-2

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