In close collaboration of several groups, kinetic experiments will be performed and used to parameterize kinetic models, the thermodynamic behavior of the mixtures will be modeled and on this basis a first optimization of the reactor and of the flowsheet will be conducted. Based on first experiments and process models, promising operating windows that lead to an economically viable process will be identified. The optimization will be performed using the Flowsheet Superstructure Optimization platform FSOpt which was developed in the first two funding periods (subproject C1E). The information from the process simulations and optimizations are used for defining maximally informative laboratory experiments and the results of these experiments are used to improve the models. The reaction part of the optimized processes will be validated at the miniplant scale in subprojects D2 and D3. The results of the miniplant experiments will provide information for further improving the designed process flowsheets.

It is expected that this close interdisciplinary connection between design of experiments, model development and process optimization will significantly reduce the experimental effort and the time for process development.

Based on the experience gained from the two case studies, the tools and methods for modelling thermodynamic properties and reaction kinetics, optimization of the reaction step and process design under uncertainties will be integrated into an iterative procedure for process design driven by model-based economic optimization.

Connected projects within Collaborative Research Centre/Transregio 63

A2 (Schomäcker): Influence of catalyst ligand complexes, network analysis of total and sub reaction networks, evaluation of catalyst deactivation

A3 (Hamel, Seidel-Morgenstern): Mechanistic and Kinetic Investigations of the Isomerization, Hydroformylation and Hydroesterification of Petrochemicals and Oleochemicals in Multiphase Fluid Systems

A4 (Sadowski, Stein): Reaction Kinetics and Phase Equilibria in Complex Mixtures

A9 (Enders, Sadowski): Solubilization of weakly polar compounds in micellar systems

A10 (Böhm, Hecht, Kraume): Gas/Liquid Mass Transfer in Reactive Multiphase Systems

A11 (Seidensticker, Vogt): Homogeneously catalyzed reductive amination of long-chain aldehydes and hydroaminomethylation of long-chain alkenes with integrated catalyst separation in thermoregulated phase systems

B1 (Sundmacher, Zähringer): Exchange of kinetic data and models, validation of the optimal solvent system as well as dosing and temperature trajectories on reactor and process level

B8 (Kraume, Thévenin): Characterization, modeling and simulation of phase separation in micellar multiphase systems

B9 (Kienle, Sundmacher): Integrated design of thermomorphic multicomponent systems (TMS) and separation processes for the efficient recovery of homogeneous catalysts and solvents

D2 (Repke): Demonstration of the Fast Track Process Development and of the Optimal Operation of the Reductive Amination of Long-chained Aldehydes in Emulsion Systems

D3 (Skiborowski, Vogt): Development and testing of integrated reaction and catalyst separation for the homogenously catalyzed reductive amination and hydroaminomethylation of long chain alkenes in a miniplant

D4 (Engell, Esche): Control and optimal operation of the reductive amination and of the hydroaminomethylation in the demonstration plants

Recent Publications

Huxoll, F.; Jameel, F.; Bianga, J.; Seidensticker, T.; Stein, M.; Sadowski, G.; Vogt, D.; Solvent Selection in Homogeneous Catalysis—Optimization of Kinetics and Reaction Performance. ACS Catalysis 11, 2, 590-594, 2021. [DOI: 10.1021/acscatal.0c04431]

Janus, T.; Engell, S. Iterative Process Design with Surrogate-AssistedGlobal Flowsheet Optimization. Chemie Ingenieur Technik, 93, 2018-2028, 2021. [DOI:10.1002/cite.202100095]

Janus, T.; Riedl, F.; Engell, S. Generation and Benefit of Surrogate Models for Blackbox Chemical Flowsheet Optimization. Computer-aided Chemical Engineering, 49, 1561-1566, 2022. [conference paper]

Kaiser, S.; Menzel, T.; Engell, S. Focusing experiments in the early phase process design by process optimization and global sensitivity analysis. Computer Aided Chemical Engineering, 50, 899-904, 2021. [DOI:10.1016/B978-0-323-88506-5.50139-X]

Kaiser, S.; Engell, S. Integrating Superstructure Optimization under Uncertainty and Optimal Experimental Design in early Stage Process 
Development. Computer Aided Chemical Engineering 48, 799-804, 2020. [doi.org/10.1016/B978-0-12-823377-1.50134-8]

Janus, T.; Cegla, M.; Barkmann, S.; Engell, S. Optimization of a hydroformulation process in a thermomorphic solvent system using a commercial steady-state process simulator and a memetic algorithm. 29th European Symposium on Computer Aided Process Engineering, 29, 469-474, 2019. [DOI: 10.1016/B978-0-12-818634-3.50079-5]

Nentwich, C.; Engell, S. Surrogate modeling of phase equilibrium calculations using adaptive sampling. Comput. Chem. Eng., 126, 204–217, 2019. [doi.org/10.1016/j.compchemeng.2019.04.006]

Nentwich, C.; Winz, J.; Engell, S.  Surrogate Modeling of Fugacity Coefficients Using Adaptive Sampling. Industrial & Engineering Chemistry Research 58 (40), 18703-18716,  2019. [DOI: 10.1021/acs.iecr.9b02758]