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In silico screening of carbon-capture materials

Nature Materials volume 11, pages 633–641 (2012)Cite this article

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Abstract

One of the main bottlenecks to deploying large-scale carbon dioxide capture and storage (CCS) in power plants is the energy required to separate the CO2 from flue gas. For example, near-term CCS technology applied to coal-fired power plants is projected to reduce the net output of the plant by some 30% and to increase the cost of electricity by 60–80%. Developing capture materials and processes that reduce the parasitic energy imposed by CCS is therefore an important area of research. We have developed a computational approach to rank adsorbents for their performance in CCS. Using this analysis, we have screened hundreds of thousands of zeolite and zeolitic imidazolate framework structures and identified many different structures that have the potential to reduce the parasitic energy of CCS by 30–40% compared with near-term technologies.

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Figure 1: Hybrid pressure and temperature swing adsorption.
Figure 2: (Mixture) adsorption isotherms.
Figure 3: Parasitic energy as a function of the Henry coefficient of CO2 for all silica zeolite structures.
Figure 4: Adsorption isotherms.
Figure 5: Optimal materials.
Figure 6: Parasitic energy for zeolites with cations.
Figure 7: Parasitic energy for ZIFs.

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Acknowledgements

The research was supported by the US Department of Energy under contracts DE-AC02-05CH11231, #CSNEW918, DE-SC0001015, DE-FG02-03ER15456, ARPA-e, and CCSI and the Office of Innovation at the Electric Power Research Institute (a detailed description can be found in the Supplementary Information).

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Author notes

  1. Li-Chiang Lin, Adam H. Berger, Richard L. Martin and Jihan Kim: These authors contributed equally to this work

Authors and Affiliations

  1. Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720-1462, USA

    Li-Chiang Lin, Joseph A. Swisher & Berend Smit

  2. Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA

    Li-Chiang Lin, Jihan Kim, Joseph A. Swisher, Kuldeep Jariwala & Berend Smit

  3. Electric Power Research Institute (EPRI), 3420 Hillview Avenue, Palo Alto, California 94304, USA

    Adam H. Berger & Abhoyjit S. Bhown

  4. Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720-8139, USA

    Richard L. Martin, Chris H. Rycroft & Maciej Haranczyk

  5. Department of Mathematics, University of California, Berkeley, California 94720, USA

    Chris H. Rycroft

  6. Departments of Bioengineering and Physics and Astronomy, Rice University, Houston, Texas 77005, USA

    Michael W. Deem

  7. Department of Chemistry, University of California, Berkeley, California 94720-1462, USA

    Berend Smit

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All authors contributed significantly to the work presented in this paper.

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Correspondence to Li-Chiang Lin, Richard L. Martin, Jihan Kim or Berend Smit.

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Lin, LC., Berger, A., Martin, R. et al. In silico screening of carbon-capture materials. Nature Mater 11, 633–641 (2012). https://doi.org/10.1038/nmat3336

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