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MOFIA: a chemoinformatic webserver for the prediction of CO2 adsorption in metal organic frameworks (MOF)

Published online by Cambridge University Press:  07 February 2013

Michael Fernandez
Affiliation:
Centre for Catalysis Research and Innovation, Department of Chemistry, University of Ottawa, Ottawa, Canada
Tom D Daff
Affiliation:
Centre for Catalysis Research and Innovation, Department of Chemistry, University of Ottawa, Ottawa, Canada
Nicholas R. Trefiak
Affiliation:
Centre for Catalysis Research and Innovation, Department of Chemistry, University of Ottawa, Ottawa, Canada
Tom K. Woo
Affiliation:
Centre for Catalysis Research and Innovation, Department of Chemistry, University of Ottawa, Ottawa, Canada
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Abstract

Nanoporous metal-organic framework (MOF) materials are strong candidates for energy efficient carbon capture and storage (CCS) technologies. A total of ∼20,000 hypothetical MOFs were ab initio screened for CO2 adsorption using grand canonical Monte-Carlo (GCMC) simulations. Novel radial distribution function (RDF) scores were modified for periodic systems to predict the CO2 adsorption of MOFs using chemoinformatic models. The test set predictions yielded accuracies of 0.76 and 0.85 at 0.1 bar and 1 bar, respectively. The models were used to screen a large database for high performing MOFs and the top 100 structures were successfully validated by GCMC simulations. The chemoinformatic predictors of the CO2 adsorption of MOFs are available online at http://titan.chem.uottawa.ca/woolab/MOFIA/#carbondioxide.

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Articles
Copyright
Copyright © Materials Research Society 2013

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MOFIA: a chemoinformatic webserver for the prediction of CO2 adsorption in metal organic frameworks (MOF)
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