Publikationen Forschungsgruppe PSE

Abel, K. L.; Beger, T.; Poppitz, D.; Zimmermann, R. T.; Kuschel, O.; Sundmacher, K.; Gläser, R.: Monolithic Al2O3 Xerogels with Hierarchical Meso‐/Macropore System as Catalyst Supports for Methanation of CO₂. ChemCatChem (2022)

Chai, S.; Song, Z.; Zhou, T.; Zhang, L.; Qi, Z.: Computer-aided molecular design of solvents for chemical separation processes. Current Opinion in Chemical Engineering 35, 100732 (2022)

Hessel, V.; Tran, N. N.; Asrami, M. R.; Tran, Q. D.; Van Duc Long, N.; Escribà-Gelonch, M.; Tejada, J. O.; Linke, S.; Sundmacher, K.: Sustainability of green solvents – review and perspective. Green Chemistry 24, S. 410 - 437 (2022)

Himmel, A.; Findeisen, R.; Sundmacher, K.: Closed-loop real-time optimization for unsteady operating production systems. Journal of Process Control 113, S. 80 - 95 (2022)

Keßler, T.; Kunde, C.; Linke, S.; Sundmacher, K.; Kienle, A.: Integrated computer-aided molecular and process design: Green solvents for the hydroformylation of long-chain olefines. Chemical Engineering Science 249, 117243 (2022)

Marušič, N.; Otrin, L.; Rauchhaus, J.; Zhao, Z.; Kyrilis, F. L.; Hamdi, F.; Kastritis, P. L.; Dimova, R.; Ivanov, I.; Sundmacher, K.: Increased efficiency of charge-mediated fusion in polymer/lipid hybrid membranes. Proceedings of the National Academy of Sciences 119 (20), e2122468119 (2022)

Marušič, N.; Zhao, Z.; Otrin, L.; Dimova, R.; Ivanov, I.; Sundmacher, K.: Fusion‐Induced Growth of Biomimetic Polymersomes: Behavior of Poly(dimethylsiloxane)‐Poly(ethylene oxide) Vesicles in Saline Solutions Under High Agitation. Macromolecular Rapid Communications 43 (5), e2100712 (2022)

Papakonstantinou, G.; Spanos, I.; Dam, A. P.; Schlögl, R.; Sundmacher, K.: Electrochemical evaluation of the de-/re-activation of oxygen evolving Ir oxide. Physical Chemistry Chemical Physics 24 , S. 14579 - 14591 (2022)

Qin, H.; Cheng, J.; Yu, H.; Zhou, T.; Song , Z.: Hierarchical Ionic Liquid Screening Integrating COSMO-RS and Aspen Plus for Selective Recovery of Hydrofluorocarbons and Hydrofluoroolefins from a Refrigerant Blend. Industrial & Engineering Chemistry Research 61 (11), S. 4083 - 4094 (2022)

Qin, H.; Song, Z.; Qi, Z.; Sundmacher, K.: Comparative screening of organic solvents, ionic liquids, and their binary mixtures for vitamin E extraction from deodorizer distillate. Chemical Engineering and Processing - Process Intensification 171, 108711 (2022)

Qin, H.; Wang, Z.; Song, Z.; Zhang, X.; Zhou, T.: High-Throughput Computational Screening of Ionic Liquids for Butadiene and Butene Separation. Processes 10 (1), 165 (2022)

Sanchez Medina, E. I.; Linke, S.; Stoll, M.; Sundmacher, K.: Graph neural networks for the prediction of infinite dilution activity coefficients. Digital Discovery 1 (3), S. 216 - 225 (2022)

Wang, Z.; Zhou, T.; Sundmacher, K.: Interpretable machine learning for accelerating the discovery of metal-organic frameworks for ethane/ethylene separation. Chemical Engineering Journal 444, 136651 (2022)

Wang, Z.; Zhou, Y.; Zhou, T.; Sundmacher, K.: Identification of Optimal Metal-Organic Frameworks by Machine Learning: Structure Decomposition, Feature Integration, and Predictive Modeling. Computers & Chemical Engineering 160, 107739 (2022)

Weber, S.; Zimmermann, R. T.; Bremer, J.; Abel, K. L.; Poppitz, D.; Prinz, N.; Ilsemann, J.; Wendholt, S.; Yang, Q.; Pashminehazar, R. et al.; Monaco, F.; Cloetens, P.; Huang, X.; Kübel, C.; Kondratenko, E.; Bauer, M.; Bäumer, M.; Zobel, M.; Gläser, R.; Sundmacher, K.; Sheppard, T. L.: Digitization in Catalysis Research: Towards a Holistic Description of a Ni/Al2O3 Reference Catalyst for CO2 Methanation. ChemCatChem 14 (8), e202101878 (2022)

Wen, H.; Su, Y.; Wang, Z.; Jin, S.; Ren, J.; Shen, W.; Eden, M.: A systematic modeling methodology of deep neural network‐based structure‐property relationship for rapid and reliable prediction on flashpoints. AIChE Journal 68 (1), 17402 (2022)

Xu, J.; Rong, S.; Sun, J.; Peng, Z.; Jin, H.; Guo, L.; Zhang, X.; Zhou, T.: Optimal design of non-isothermal supercritical water gasification reactor: From biomass to hydrogen. Energy 244, 123163 (2022)

Yang, A.; Su, Y.; Shi, T.; Ren, J.; Shen, W.; Zhou, T.: Energy-efficient recovery of tetrahydrofuran and ethyl acetate by triple-column extractive distillation: entrainer design and process optimization. Frontiers of Chemical Science and Engineering 16, S. 303 - 315 (2022)

Zhang, X.; Zhou, T.; Sundmacher, K.: Integrated metal–organic framework and pressure/vacuum swing adsorption process design: Descriptor optimization. AIChE Journal 68 (2), e17524 (2022)

Zhou, Y.; Zhang, X.; Zhou, T.; Sundmacher, K.: Computational Screening of Metal-Organic Frameworks for Ethylene Purification from Ethane/Ethylene/Acetylene Mixture. Nanomaterials 12 (5), 869 (2022)

Zimmermann, R. T.; Bremer, J.; Sundmacher, K.: Load-flexible fixed-bed reactors by multi-period design optimization. Chemical Engineering Journal 428, 130771 (2022)

Kraume, M.; Enders, S.; Drews, A.; Schomäcker, R.; Engell, S.; Sundmacher, K. (Hg.): Integrated Chemical Processes in Liquid Multiphase Systems From Chemical Reaction to Process Design and Operation. De Gruyter, Berlin/Boston (2022), 622 S.

Sundmacher, K.: Wasserstoff-Technologien: Bausteine einer CO₂-neutralen Energieversorgung. Technikwissenschaftliche Vorlesung, Berlin-Brandenburgische Akademie der Wissenschaften, Berlin (2022)

Bankala, R.: Multi-objective optimization of an organic Rankine cycle system using Gaussian processes. Master (2022)

Zhou, T.; Sundmacher, K.: Multiscale process systems engineering—analysis and design of chemical and energy systems from molecular design up to process optimization. Frontiers of Chemical Science and Engineering 16, S. 137 - 140 (2022)