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An Inverse Analysis Approach to the Characterization of Chemical Transport in Paints
Published on: August 29, 2014
Predicting adsorption coefficients of VOCs using polyparameter linear free energy relationship based on the
Huijuan Liu1, Keyan Wei1, Yansong Yu1
1State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China.
Abstract:
Predicting adsorption of volatile organic compounds (VOCs) on activated carbons is of major importance to understand activated carbons' adsorption properties and explore their potential applications. In this study, adsorption of 38 VOCs on a commercial granular activated carbon (GAC) was examined using inverse gas chromatography (IGC) at infinite dilution, and the adsorption coefficients (K), dispersive and specific components of adsorption free energy were calculated. We found that the dispersive interaction was well described by adsorbate's molar polarizability (P), and the specific interactions well by dipolarity/polarizability (S), hydrogen-bond acidity (A) and hydrogen-bond basicity (B). Based on the result, a polyparameter linear free energy relationship (PP-LFER) was established: logK = (0.96 ± 0.23) S + (2.23 ± 0.34) A + (0.84 ± 0.25) B + (0.69 ± 0.050) P + (0.13 ± 0.35); (n = 38, R2 = 0.859, root mean square error (RMSE) = 0.25), which exhibited a more accurate prediction compared to the classical PP-LFER (E, S, A, B and L as descriptors, R2 = 0.765, RMSE = 0.33). Moreover, it overcame the drawbacks of indistinguishable dispersive interaction and unavailable relative contribution of each interaction for classical PP-LFER in explaining adsorption mechanism. As suggested by the developed model, the dispersive interaction was the dominant contribution to the adsorption of VOCs on GAC (42-100%), following by dipole-type interactions (0-30%) and hydrogen bonding (hydrogen-bond acidity 0-32%, hydrogen-bond basicity 0-11%). Additionally, it also accurately predicted the K values of VOCs on other three activated carbons.
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