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Enzyme-catalyzed reactive distillation: extension to multistep chemoenzymatic processes

Subject Area Chemical and Thermal Process Engineering
Biological Process Engineering
Term from 2011 to 2019
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 210092096
 
Final Report Year 2019

Final Report Abstract

Main results obtained in the 3rd project: a) Selection of an appropriate model reaction for the dynamic kinetic resolution: Based on our preselection tool, chemoenzymatic DKR of (R/S)-2-PeOH with EtBu in p-xylene in a distillation approach is selected. The adjustment of a temperature difference allows beneficial temperature conditions for both the chemo- (Shvo) as well as biocatalyst (NZ435). b) Development and evaluation of an immobilization method for the isomerization catalyst in the dynamic kinetic resolution: No immobilization is considered, because of spatial separation technique and necessity of homogenously dissolved application of the chemocatalyst. c) Development of an inline analytical tool using FTIR spectroscopy for application in reactive distillation processes: Spatial resolved inline FTIR analytics was successfully developed for the reactive distillation process, enabling rpcess control in respect to conversion and catalyst deactivation at different heights in the RD column. d) Implementation of the dynamic kinetic resolution reaction in the reactive distillation column with a chemo-enzymatic or a double enzymatic catalysis: Successful performance of chemo-enzymatic DKR with an applied T-difference is achieved at two different positions of NZ435 in the distillation setup. An optimal operation window at starting molar fractions in the range of 0.6 mol∙mol^-1 < x(R/S)-2-PeOH,0 < 0.67 mol∙mol^-1 is obtained for the kinetic resolution of (R/S)-2-PeOH with PrBu in reactive distillation. e) Development of a simulation model for dynamic batch operation of reactive distillation processes with enzymes: The simulation model for dynamic EtBu -> R-2-PeBu transesterification with the use of ERD was developed and successfully validated with experimental data. Simulations have shown that the amount of catalyst, column height, effective reflux ratio, reboiler duty, and starting mixture composition all significantly affect the conversion rates of substrates, and should be taken into account in process optimization.

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