Publication date: Mar 24, 2020
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 |
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properties_COFs.csv
MD5md5:dff07dc03c138200b4e88c0e085af2ce
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6.2 MiB | Basic Properties of all COFs studied (includes all COFs in Figure 1 of the paper ) |
properties_COFs_subset.csv
MD5md5:f5ce89d2a6105ce723352f352d645db4
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105.4 KiB | Properties from molecular simulations for a subset of COFs (includes all COFs in Figure 3 of the paper) |
export_hcofs_co2.aiida
MD5md5:31a46b296a826080fc2c56e439bc0665
Open this AiiDA archive on renkulab.io (https://renkulab.io/)
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6.9 GiB | AiiDA v1.0.1 export file |
2020.0029/v1 (version v1) [This version] | Mar 24, 2020 | DOI10.24435/materialscloud:2020.0029/v1 |