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In silico discovery of covalent organic frameworks for carbon capture

Kathryn S. Deeg1, Daiane Damasceno Borges2, Daniele Ongari3*, Nakul Rampal4, Leopold Talirz3, Aliaksandr V. Yakutovich3, Johanna M. Huck1, Berend Smit3

1 Department of Chemistry, University of California, Berkeley, California, 94720, United States

2 Instituto de Física, Universidade Federal de Uberlândia, Uberlândia-MG 38408-100, Brasil

3 Laboratory of Molecular Simulation (LSMO), Institut des sciences et ingénierie chimiques (ISIC), Ecole polytechnique fédérale de Lausanne (EPFL) Valais, Rue de l’Industrie 17, 1951, Sion, Switzerland

4 Adsorption and Advanced Materials Laboratory (AAML), Department of Chemical Engineering Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, UK

* Corresponding authors emails: daniele.ongari@epfl.ch
DOI10.24435/materialscloud:2020.0029/v1 [version v1]

Publication date: Mar 24, 2020

How to cite this record

Kathryn S. Deeg, Daiane Damasceno Borges, Daniele Ongari, Nakul Rampal, Leopold Talirz, Aliaksandr V. Yakutovich, Johanna M. Huck, Berend Smit, In silico discovery of covalent organic frameworks for carbon capture, Materials Cloud Archive 2020.0029/v1 (2020), doi: 10.24435/materialscloud:2020.0029/v1.


We screen a database of more than 69,000 hypothetical covalent organic frameworks (COFs) for carbon capture, using parasitic energy as a metric. In order to compute CO2-framework interactions in molecular simulations, we develop a genetic algorithm to tune the charge equilibration method and derive accurate framework partial charges. Nearly 400 COFs are identified with parasitic energy lower than that of an amine scrubbing process using monoethanolamine; over 70 are better performers than the best experimental COFs; and several perform similarly to Mg-MOF-74. We analyze the effect of pore topology on carbon capture performance in order to guide development of improved carbon capture materials.


File name Size Description
6.2 MiB Basic Properties of all COFs studied (includes all COFs in Figure 1 of the paper )
105.4 KiB Properties from molecular simulations for a subset of COFs (includes all COFs in Figure 3 of the paper)
6.9 GiB AiiDA v1.0.1 export file


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Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.


computational screening MARVEL/DD4 gas adsorption covalent organic frameworks cofs ERC

Version history:

2020.0029/v1 (version v1) [This version] Mar 24, 2020 DOI10.24435/materialscloud:2020.0029/v1