Schlüter, D.; Schulze-Niemand, E.; Stein, M.; Naumann, M.: Ovarian tumor domain proteases in pathogen infection. Trends in Microbiology 30 (1), S. 22 - 33 (2022)

Schneider, P.; Bekiaris, P. S.; Kamp von, A.; Klamt, S.: StrainDesign: a Comprehensive Python Package for Computational Design of Metabolic Networks. Bioinformatics 38 (21), S. 4981 - 4983 (2022)

Schulze-Niemand, E.; Naumann, M.; Stein, M.: Substrate‐assisted activation and selectivity of the bacterial RavD effector deubiquitinylase. Proteins: Structure, Function, and Bioinformatics 90 (4), S. 947 - 958 (2022)

Scoma, A.; Khor, W.; Coma, M.; Heyer, R.; Props, R.; Bouts, T.; Benndorf, D.; Li, D.; Zhang, H.; Rabaey, K.: Lignocellulose Fermentation Products Generated by Giant Panda Gut Microbiomes Depend Ultimately on pH Rather than Portion of Bamboo: A Preliminary Study. Microorganisms 10 (5), 978 (2022)

Seidel, C.; Nikolić, D.; Felischak, M.; Petkovska, M.; Seidel-Morgenstern, A.; Kienle, A.: Forced Periodic Operation of Methanol Synthesis in an Isothermal Gradientless Reactor. Chemical Engineering & Technology 45 (12), S. 2261 - 2272 (2022)

Smit, A. T.; Verges, M.; Schulze, P.; van Zomeren, A.; Lorenz, H.: Laboratory- to Pilot-Scale Fractionation of Lignocellulosic Biomass Using an Acetone Organosolv Process. ACS Sustainable Chemistry & Engineering 10 (32), S. 10503 - 10513 (2022)

Song , Z.; Long, N. V. D.; Qin, H.; Tran, N. N.; Fulcheri, L.; Hessel, V.; Sundmacher, K.: Thermal-plasma-assisted renewable hydrogen and solid carbon production from ionic liquid-based biogas upgrading: A process intensification study. Chemical Engineering and Processing - Process Intensification 180, 108777 (2022)

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)

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)