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Molecular interactions of alcohols with zeolite BEA and MOR frameworks
Authors:Kai Stückenschneider  Juliane Merz  Gerhard Schembecker
Affiliation:1. Laboratory of Plant and Process Design, Department of Biochemical and Chemical Engineering, TU Dortmund University, 44227, Dortmund, Germany
Abstract:
Zeolites can adsorb small organic molecules such as alcohols from a fermentation broth. Also in the zeolite-catalyzed conversion of alcohols to biofuels, biochemicals, or gasoline, adsorption is the first step. Several studies have investigated the adsorption of alcohols in different zeolites experimentally, but computational investigations in this field have mostly been restricted to zeolite MFI. In this study, the adsorption of C1–C4 alcohols in BEA and MOR was investigated using density functional theory (DFT). Calculated adsorption geometries and the corresponding energies of the designed cluster models were comparable to periodic calculations, and the adsorption energies were in the same range as the corresponding computational and experimental values reported in the literature for zeolite MFI. Thus, BEA and MOR may be good adsorption materials for alcohols in the field of downstream processing and catalysis. Aside from the DFT calculations, adsorption isotherms were determined experimentally in this study from aqueous solutions. For BEA, the adsorption of significant amounts of alcohol from aqueous solution was observed experimentally. In contrast, MOR was loaded with only a very small amount of alcohol. Although differences were found between the affinities obtained from gas-phase DFT calculations and those observed experimentally in aqueous solution, the computational data presented here represent molecular level information on the geometries and energies of C1–C4 alcohols adsorbed in zeolites BEA and MOR. This knowledge should prove very useful in the design of zeolite materials intended for use in adsorption and catalytic processes, as it allows adsorption behavior to be predicted via judiciously designed computational models.
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