Publications of Kai Sundmacher

Wang, Z., Zhou, T., & Sundmacher, K. (2023)Molecular Property Targeting for Optimal Solvent Design in Extractive Distillation ProcessesIn: 33rd European Symposium on Computer Aided Process Engineering: Computer Aided Chemical Engineering, 1247–1252doi: 10.1016/B978-0-443-15274-0.50199-2.

Zhang, X. & Sundmacher, K. (2023)Optimal Design of Anion-pillared Metal-organic Frameworks for Gas SeparationIn: 33rd European Symposium on Computer Aided Process Engineering, 991–996doi: 10.1016/B978-0-443-15274-0.50158-X.

Wang, Z., Zhou, T., & Sundmacher, K. (2022)A Novel Machine Learning-Based Optimization Approach for the Molecular Design of SolventsIn: 32nd European Symposium on Computer Aided Process Engineering, 1477–1482doi: 10.1016/B978-0-323-95879-0.50247-2.

Zhang, X., Zhou, T., & Sundmacher, K. (2022)Metal-Organic Framework Targeting for Optimal Pressure Swing Adsorption ProcessesIn: 14th International Symposium on Process Systems Engineering: 295–300doi: 10.1016/B978-0-323-85159-6.50049-X.

Zhou, T., Wang, Z., & Sundmacher, K. (2022)A New Machine Learning Framework for Efficient MOF Discovery: Application to Hydrogen StorageIn: 14th International Symposium on Process Systems Engineering: 1807–1812doi: 10.1016/B978-0-323-85159-6.50301-8.

Zimmermann, R. T., Bremer, J., & Sundmacher, K. (2022)Optimal Catalyst-Reactor Design for Load-Flexible CO2 Methanation by Multi-Period Design OptimizationIn: 14th International Symposium on Process Systems Engineering: 841–846doi: 10.1016/B978-0-323-85159-6.50140-8.

Balasbas III, S., Ivanov, I., & Sundmacher, K. (2021)Metabolic Network Reconstruction from Time-Series of Concentration Data: Evaluation of the Numerical Matrices MethodsIn: 31st European Symposium on Computer Aided Process Engineering, 1991–1996doi: 10.1016/B978-0-323-88506-5.50308-9.

Bremer, J., Heiland, J., Benner, P., & Sundmacher, K. (2021)Non-intrusive Time Galerkin POD for Optimal Control of a Fixed-Bed Reactor for CO₂ MethanationIn: IFAC-PapersOnLine, 122–127doi: 10.1016/j.ifacol.2021.08.229.

Sanchez Medina, E. I., Linke, S., & Sundmacher, K. (2021)Prediction of Bioconcentration Factors (BCF) using Graph Neural NetworksIn: 31st European Symposium on Computer Aided Process Engineering, 991–997doi: 10.1016/B978-0-323-88506-5.50153-4.

Sanchez Medina, E. I., Vallejo, D. R., Chachuat, B., Sundmacher, K., Petsagkourakis, P., & del Rio-Chanona, E. A. (2021)Acyclic modular flowsheet optimization using multiple trust regions and Gaussian process regressionIn: 31st European Symposium on Computer Aided Process Engineering, 1117–1123doi: 10.1016/B978-0-323-88506-5.50172-8.

Song, Z., Zhou, T., Qi, Z., & Sundmacher, K. (2021)Computer-Aided Screening of Deep Eutectic Solvent Systems for the Associative Extraction of α-Tocopherol from Deodorizer DistillateIn: 31st European Symposium on Computer Aided Process Engineering, 341–346doi: 10.1016/B978-0-323-88506-5.50054-1.

Zhou, T., Shi, H., & Sundmacher, K. (2021)Rational Design of Ionic Liquid Phase-Change Material for Efficient Thermal Energy StorageIn: 31st European Symposium on Computer Aided Process Engineering, 191–196doi: 10.1016/B978-0-323-88506-5.50031-0.

Zimmermann, R. T., Bremer, J., & Sundmacher, K. (2021)Multi-Period Design Optimization of Flexible Fixed-Bed Reactors by Stoichiometry-Based Model ReductionIn: 31st European Symposium on Computer Aided Process Engineering, 947–952doi: 10.1016/B978-0-323-88506-5.50146-7.

Keßler, T., Kunde, C., Linke, S., McBride, K., Sundmacher, K., & Kienle, A. (2020)Computer Aided Molecular Design of Green Solvents for the Hydroformylation of Long-Chain OlefinesIn: 30th European Symposium on Computer Aided Process Engineering: Computer Aided Chemical Engineering, 745–750doi: 10.1016/B978-0-12-823377-1.50125-7.

Maggi, A., Wenzel, M., & Sundmacher, K. (2020)Power-to-Syngas Processes by Reactor-Separator Superstructure OptimizationIn: 30th European Symposium on Computer Aided Process Engineering, 1387–1392doi: 10.1016/B978-0-12-823377-1.50232-9.

Matschek, J., Himmel, A., Sundmacher, K., & Findeisen, R. (2020)Constrained Gaussian Process Learning for Model Predictive ControlIn: IFAC-PapersOnLine, 971–976doi: 10.1016/j.ifacol.2020.12.1269.

Zhou, Y., Zhou, T., & Sundmacher, K. (2020)In silico Screening of Metal-organic Frameworks for Acetylene/ethylene SeparationIn: 30th European Symposium on Computer Aided Process Engineering, 895–900doi: 10.1016/B978-0-12-823377-1.50150-6.

Bechtel, S., Song, Z., Zhou, T., Vidaković-Koch, T., & Sundmacher, K. (2018)Integrated Process and Ionic Liquid Design by Combining Flowsheet Simulation with Quantum-Chemical Solvent ScreeningIn: 13th International Symposium on Process Systems Engineering (PSE 2018), 2167–2172doi: 10.1016/B978-0-444-64241-7.50356-6.

Liesche, G., Schack, D., Rätze, K., & Sundmacher, K. (2018)Thermodynamic Network Flow Approach for Chemical Process SynthesisIn: 28th European Symposium on Computer Aided Process Engineering, 881–886doi: 10.1016/B978-0-444-64235-6.50154-6.

McBride, K., Linke, S., Xu, S., & Sundmacher, K. (2018)Computer Aided Design of Green Thermomorphic Solvent Systems for Homogeneous Catalyst RecoveryIn: 13th International Symposium on Process Systems Engineering (PSE 2018), 1783–1788doi: 10.1016/B978-0-444-64241-7.50292-5.