Energy efficient Separation in the chemical and pharmaceutical Industry using MEMbrane processes (ESIMEM)
The project "Energy Efficient Separation in the Chemical and Pharmaceutical Industry with MEMBRAN-Processes" (ESIMEM), funded by the German Federal Ministry of Economics and Energy (BMWi), focused on the implementation of nanofiltration with organic solvents (OSN) within the "standard toolbox" of the unit operations considered for process design. Therefore, the project worked on a standardized measurement methodology and the development of systematic evaluation procedures to reliably determine and quantify the separation properties of a membrane. In addition, tools for conceptual process design, detailed process modeling and cost estimation were developed. The focus of the own work was on the development of shortcut methods that allow the prediction of the separation properties of a membrane based on existing flow and retention data for alternative solvents and dissolved components.
Cooperation partners: RWTH Aachen, TU Berlin, Helmholtz-Zentrum Geesthacht, Fraunhofer IKTS, Fa. Junghans, Merck und Evonik
Funded by: Federal Ministry of Economics and Energy (BMWi) through Prof. Dr.-Ing. Andrzej Górak (2015-2017)
Publications:
Goebel, R. and Glaser, T. and Niederkleine, I. and Skiborowski, M. (2018). Towards predictive models for organic solvent nanofiltration. Computer Aided Chemical Engineering. 43 115--120. [doi][www][BibTex]
Bertleff, B. and Goebel, R. and Claußnitzer, J. and Korth, W. and Skiborowski, M. and Wasserscheid, P. and Jess, A. and Albert, J. (2018). Investigations on Catalyst Stability and Product Isolation in the Extractive Oxidative Desulfurization of Fuels Using Polyoxometalates and Molecular Oxygen. ChemCatChem. 10 (20), 4602--4609. [doi][www][BibTex]
Goebel, R. and Schreiber, M. and Koleva, V. and Horn, M. and Górak, A. and Skiborowski, M. (2019). On the reliability of lab-scale experiments for the determination of membrane specific flux measurements in organic solvent nanofiltration. Chemical Engineering Research and Design. 148 271--279. [doi][www][BibTex]
Böcking, A. and Koleva, V. and Wind, J. and Thiermeyer, Y. and Blumenschein, S. and Goebel, R. and Skiborowski, M. and Wessling, M. (2019). Can the variance in membrane performance influence the design of organic solvent nanofiltration processes?. Journal of Membrane Science. 575 217--228. [doi][www][BibTex]
Goebel, R. and Skiborowski, M. (2020). Machine-based learning of predictive models in organic solvent nanofiltration: Pure and mixed solvent flux. Separation and Purification Technology. 237[doi][www][BibTex]
Goebel, R. and Glaser, T. and Skiborowski, M. (2020). Machine-based learning of predictive models in organic solvent nanofiltration: Solute rejection in pure and mixed solvents. Separation and Purification Technology. 248[doi][www][BibTex]
