(704a) Effect of Functional Groups on Separating CO2 from CO2/N2 Mixtures Using Edge Functionalized Graphene Nanoribbons

Development of microporous adsorbents for separation and sequestration of carbon dioxide from flue gas streams is an area of active research. In this study, we assess the influence of specific functional groups on the adsorption selectivity of CO2/N2 mixtures through Grand-Canonical Monte Carlo (GCMC) simulations. Our model system consists of a bilayer graphene nanoribbon that has been edge functionalized with OH, NH2, NO2, CH3 and COOH. Ab initio Møller-Plesset (MP2) calculations with functionalized benzenes are used to obtain binding energies and optimized geometries for CO2 and N2. These information in turn are used to validate the choice of the classical forcefield in the GCMC simulations. In addition to simulations of adsorption from binary mixtures of CO2 and N2, the ideal adsorbed solution theory (IAST) is used to predict mixture isotherms. Our study reveals that functionalization always leads to an increase in the adsorption of both CO2 and N2 with the highest for COOH. However, significant enhancement in the selectivity for CO2is only seen with COOH functionalized nanoribbons. The COOH functionalization gives a 28% increase in selectivity compared to H terminated nanoribbons, whereas the improvement in the selectivity for other functional groups are much more modest. Our study suggests that specific functionalization with COOH groups can provide a materials design strategy to improve CO2 selectivity in microporous adsorbents. Synthesis of graphene nanoplatelets with edge functionalized COOH, which has the potential for large scale produciton has recently been reported.