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Gräßler, I., Wiechel, D., Koch, A.-S., Sturm, T., &; Markfelder, T. (2023). Methodology for Certification-Compliant Effect-Chain Modeling. Systems, 11(3), Article 154.https://doi.org/10.3390/systems11030154 
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Andreiev, A., Hoyer, K.-P., Hengsbach, F., Haase, M., Tasche, L., Duschik, K., &; Schaper, M. (2023). Powder bed fusion of soft-magnetic iron-based alloys with high silicon content. Journal of Materials Processing Technology, 317, Article 117991.https://doi.org/10.1016/j.jmatprotec.2023.117991 
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Soyka, C., Ullrich, M., Striewe, M., &; Schaper, N. (2023). Comparison of Required Competences and Task Material in Modeling Education. Enterprise Modelling and Information Systems Architectures, 18, Article 7.https://doi.org/10.18417/EMISA.18.7 
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Franke, P., Shabanilemraski, I., Schubert, M., Hampel, U., &; Kenig, E. Y. (2023). A new approach to model the fluid dynamics in sandwich packings. Chemical Product and Process Modeling, 0(0).https://doi.org/10.1515/cppm-2023-0054 
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Lenz, P., Kreutzheide, P., &; Mahnken, R. (2023). Multiphase elasto-plastic mean-field homogenisation and its consistent linearisation. Computers &;amp; Structures, 290, Article 107160.https://doi.org/10.1016/j.compstruc.2023.107160 
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Tao, Y., &; Winkler, M. (2023). Global smooth solutions in a three-dimensional cross-diffusive SIS epidemic model with saturated taxis at large densities. Evolution Equations and Control Theory, 12(6), 1676–1687.https://doi.org/10.3934/eect.2023031 
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Tao, Y., &; Winkler, M. (2023). Small-signal solutions to a nonlocal cross-diffusion model for interaction of scroungers with rapidly diffusing foragers. Mathematical Models and Methods in Applied Sciences, 33(01), 103–138.https://doi.org/10.1142/s0218202523500045 
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Holtmann, J., Deantoni, J., &; Fockel, M. (2022). Early timing analysis based on scenario requirements and platform models. Software and Systems Modeling.https://doi.org/10.1007/s10270-022-01002-3 
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Protte, M., Fahr, R., &; Quevedo, D. E. (2022). Behavioral Economics for Human-in-the-Loop Control Systems Design: Overconfidence and the Hot Hand Fallacy. IEEE Control Systems, 40(6), 57–76.https://doi.org/10.1109/mcs.2020.3019723 
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Soyka, C., Schaper, N., Bender, E., Striewe, M., &; Ullrich, M. (2022). Toward a Competence Model for Graphical Modeling. ACM Transactions on Computing Education, 23(1), Article 15.https://doi.org/10.1145/3567598 
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Black, T., &; Winkler, M. (2022). Global weak solutions and absorbing sets in a chemotaxis-Navier–Stokes system with prescribed signal concentration on the boundary. Mathematical Models and Methods in Applied Sciences, 32(01), 137–173.https://doi.org/10.1142/s021820252250004x 
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Hein, M., Lopes Dias, N. F., Kokalj, D., Stangier, D., Hoyer, K.-P., Tillmann, W., &; Schaper, M. (2022). On the influence of physical vapor deposited thin coatings on the low-cycle fatigue behavior of additively processed Ti-6Al-7Nb alloy. International Journal of Fatigue, 166, Article 107235.https://doi.org/10.1016/j.ijfatigue.2022.107235 
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Hein, M., Lopes Dias, N. F., Kokalj, D., Stangier, D., Hoyer, K.-P., Tillmann, W., &; Schaper, M. (2022). On the influence of physical vapor deposited thin coatings on the low-cycle fatigue behavior of additively processed Ti-6Al-7Nb alloy. International Journal of Fatigue, 166, Article 107235.https://doi.org/10.1016/j.ijfatigue.2022.107235 
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Garcke, H., Kovács, B., &; Trautwein, D. (2022). Viscoelastic Cahn–Hilliard models for tumor growth. Mathematical Models and Methods in Applied Sciences, 32(13), 2673–2758.https://doi.org/10.1142/s0218202522500634 
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Bellomo, N., Outada, N., Soler, J., Tao, Y., &; Winkler, M. (2022). Chemotaxis and cross-diffusion models in complex environments: Models and analytic problems toward a multiscale vision. Mathematical Models and Methods in Applied Sciences, 32(04), 713–792.https://doi.org/10.1142/s0218202522500166 
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Vorbohle, C., &; Gottschalk, S. (n.d.). Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems . In Proceedings of the 29th European Conference on Information Systems (ECIS). Virtual Conference/Workshop: AIS.
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Kessler, J., Calcavecchia, F., &; Kühne, T. (2021). Artificial Neural Networks as Trial Wave Functions for Quantum Monte Carlo. Advanced Theory and Simulations, 4(4), Article 2000269.https://doi.org/10.1002/adts.202000269 
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Schulze Darup, M., Alexandru, A. B., Quevedo, D. E., &; Pappas, G. J. (2021). Encrypted Control for Networked Systems: An Illustrative Introduction and Current Challenges. IEEE Control Systems, 41(3), 58–78.https://doi.org/10.1109/mcs.2021.3062956 
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