Enzyme kinetics for the transesterification of ethyl butyrate with enzyme beads, coated packing and ultrasound assistance

The use of immobilized enzymes as renewable biocatalysts is gaining attention in the scientific community. The immobilization of enzymes is necessary to avoid a complex separation and recovery of the enzymes and to also apply enzymes in an Enzymatic Reactive Distillation (ERD). The ERD helps to furt...

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Bibliographic Details
Published in:Chemical Engineering and Processing: Process Intensification
Main Authors: Wierschem, Matthias, Walz, Olga, Mitsos, Alexander, Termuehlen, Maren, Specht, Anna Lena, Kissing, Katrin, Skiborowski, Mirko
Format: Article in Journal/Newspaper
Language:English
Published: 2017
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Online Access:http://hdl.handle.net/11420/8219
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Summary:The use of immobilized enzymes as renewable biocatalysts is gaining attention in the scientific community. The immobilization of enzymes is necessary to avoid a complex separation and recovery of the enzymes and to also apply enzymes in an Enzymatic Reactive Distillation (ERD). The ERD helps to further overcome the equilibrium limitations of transesterification reactions by means of in-situ product separation. Potential mass transfer limitations caused by the immobilization can be overcome by ultrasound (US) application to form the US-assisted ERD (US-ERD). In order to evaluate the application of ERD and US-ERD this article presents the experimental investigation of the transesterification of ethyl butyrate catalyzed by the enzyme Candida antarctica lipase B for two different types of immobilizate (coated packing and enzyme beads) with and without US-assistance. Low frequency US tends to destroy the immobilizates whereas high frequency US can increase the rate of an enzymatic reaction by 50% for the coated packings. Enzyme beads do not show diffusion limitation whereas mass transfer limitations for the coated packing can be reduced by US application. A kinetic model is identified for each of the immobilizates with and without US application and the parameters of the models accurately fit to experimental data.