Suchergebnisse

Svitnič, T.; Sundmacher, K.: Renewable methanol production: Optimization-based design, scheduling and waste-heat utilization with the FluxMax approach. Applied Energy 326, 120017 (2022)

Sydor, S.; Dandyk, C.; Schwerdt, J.; Manka, P.; Benndorf, D.; Lehmann, T.; Schallert, K.; Wolf, M.; Reichl, U.; Canbay, A. et al.; Bechmann, L. P.; Heyer, R.: Discovering Biomarkers for Non-Alcoholic Steatohepatitis Patients with and without Hepatocellular Carcinoma Using Fecal Metaproteomics. International Journal of Molecular Sciences 23 (16), 8841 (2022)

Tan, Q.; Hosseini, S. A.; Seidel-Morgenstern, A.; Thévenin, D.; Lorenz, H.: Modeling ice crystal growth using the lattice Boltzmann method. Physics of Fluids 34, 013311 (2022)

Tenberg, V.; Sadeghi, M.; Seidel-Morgenstern, A.; Lorenz, H.: Bypassing thermodynamic limitations in the Crystallization-based separation of solid solutions. Separation and Purification Technology 283, 120169 (2022)

Thiele, S.; Kamp von, A.; Bekiaris, P. S.; Schneider, P.; Klamt, S.: CNApy: a CellNetAnalyzer GUI in Python for Analyzing and Designing Metabolic Networks. Bioinformatics 38 (5), S. 1467 - 1469 (2022)

Tian, T.; Liu, M.; Li, Y.; Han, J.; Ren, L.; Lorenz, H.; Wu, Q.; Chen, J.: β-Cyclodextrin carbon-based nanoparticles with a core–shell–shell structure for efficient adsorption of crystal violet and bisphenol A. Particuology 62, S. 88 - 97 (2022)

Tolonen, A. C.; Beauchemin, N.; Bayne, C.; Li, L.; Tan, J.; Lee, J.; Meehan, B. M.; Meisner, J.; Millet, Y.; LeBlanc, G. et al.; Kottler, R.; Rapp, E.; Murphy, C.; Turnbaugh, P. J.; von Maltzahn, G.; Liu, C. M.; van Hylckama Vlieg, J. E. T.: Synthetic glycans control gut microbiome structure and mitigate colitis in mice. Nature Communications 13 (1), 1244 (2022)

Vettermann, J.; Steinert, A.; Brecher, C.; Benner, P.; Saak, J.: Compact Thermo-Mechanical Models for the Fast Simulation of Machine Tools with Nonlinear Component Behavior. at-Automatisierungstechnik 70 (8), S. 692 - 704 (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)

Wehinger, G. D.; Ambrosetti, M.; Cheula, R.; Ding, Z.-B.; Isoz, M.; Kreitz, B.; Kuhlmann, K.; Kutscherauer, M.; Niyogi, K.; Poissonnier, J. et al.; Réocreux, R.; Rudolf, D.; Wagner, J.; Zimmermann, R.; Bracconi, M.; Freund, H.; Krewer, U.; Maestri, M.: Quo vadis multiscale modeling in reaction engineering? – A perspective. Chemical Engineering Research and Design 184, S. 39 - 58 (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)

Wünsche, S.; Seidel-Morgenstern, A.; Lorenz, H.: Cocrystallization of Curcuminoids with Hydroxybenzenes Pyrogallol and Hydroxyquinol: Investigations of Binary Thermal Phase Behaviors. Crystal Growth & Design 22 (5), S. 3303 - 3310 (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)

Yalçin-Özkat, G.: Computational studies with flavonoids and terpenoids as BRPF1 inhibitors: in silico biological activity prediction, molecular docking, molecular dynamics simulations, MM/PBSA calculations. SAR and QSAR in Environmental Research 33 (7), S. 533 - 550 (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.; Sethi, S.; Wang, Z.; Zhou, T.; Qi, Z.; Sundmacher, K.: A neural recommender system for efficient adsorbent screening. Chemical Engineering Science 259, 117801 (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)

Zhang, X.; Zhou, T.; Sundmacher, K.: Integrated metal‐organic framework (MOF) and pressure/vacuum swing adsorption process design:MOFmatching. AIChE Journal 68 (9), e17788 (2022)