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Development of a thermodynamic model to predict reduced surface excess adsorption isotherms in liquid phase adsorption based on a new method for characterisation of surface groups

Subject Area Chemical and Thermal Process Engineering
Term from 2017 to 2021
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 324528022
 
The aim of this project is the prediction of reduced surface excess adsorption isotherms with a validated thermodynamic model. The characterization of the chemical surface groups on the surface of the activated carbons forms the basis for those predictions. In a first step, activated carbons with different surface functionalities will be characterized by different methods. Additionally some of these carbons will be modified by oxidizing chemicals. Then excess isotherms of binary mixtures of probe molecules (toluene, methylcyclohexane and acetone) will be measured on a selection of activated carbons. With the help of these isotherms, the competition of the probe molecules for adsorption to the surface groups can be assessed. Preliminary studies showed that such experiments can qualitatively describe the polar, nonpolar and aromatic character of the activated carbon s surface. A detailed interpretation of the reduced surface excess as well as the size of the region of preferred adsorption of the probe molecules is expected to yield further insights. Additional substance properties like the number of PI-electrons, dipole moments, polarizabilities and Hansen parameters will be used to further the qualitative discussion. Also, a quantitative description of the surface groups is intended. This will lead to a thermodynamic modeling of excess isotherms on activated carbons. A group contribution model will be developed, based on the distribution of surface groups. This model is supposed to take into account functional groups of the adsorptives as well as the activated carbon surface. The model can then be fitted to the experimental excess isotherms. Besides fitting the model to the experimental data, the research is supposed to progress in the direction of a predictive model, opening the possibility of predicting excess isotherms of not experimentally examined probe molecules.
DFG Programme Research Grants
 
 

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