Publications of Luisa Peterson

Peterson, L., Gosea, I. V., Benner, P., & Sundmacher, K. (2025)Digital Twins in Process Engineering: An Overview on Computational and Numerical MethodsComputers and Chemical Engineering, 193, 108917doi: 10.1016/j.compchemeng.2024.108917.

Peterson, L., Bremer, J., & Sundmacher, K. (2024)Challenges in data-based reactor modeling: A critical analysis of purely data-driven and hybrid models for a CSTR case studyComputers & Chemical Engineering, 184, 108643doi: 10.1016/j.compchemeng.2024.108643.

Weinhold, H., Peterson, L., Müller, T. D., Wekenborg, K., Grünewald, M., & Rarey, J. (2024)Improving the Accuracy of Activity Coefficient Estimation in Specialty Chemistry Using Local EstimatorsIndustrial & Engineering Chemistry Research, 63, 7902–7914doi: 10.1021/acs.iecr.4c00372.

Gosea, I. V., Peterson, L., Goyal, P. K., Bremer, J., Sundmacher, K., & Benner, P. (2024)Learning Reduced-Order Quadratic-Linear Models in Process Engineering using Operator InferenceENUMATH 2023 Proceedings.

Peterson, L., Bremer, J., Goyal, P. K., Gosea, I. V., Benner, P., & Sundmacher, K. (2024)Learning Reduced-Order Models for Dynamic CO₂ Methanation using Operator InferenceIn: 34th European Symposium on Computer Aided Process Engineering / 15th International Symposium on Process Systems Engineering, 3319–3324doi: 10.1016/B978-0-443-28824-1.50554-8.

Peterson, L., Bremer, J., & Sundmacher, K. (2023)Hybrid modeling of the catalytic CO2 methanation using process data and process knowledgeIn: 33rd European Symposium on Computer Aided Process Engineering, 1489–1494doi: 10.1016/B978-0-443-15274-0.50237-7.

Peterson, L., Bremer, J., Goyal, P. K., Gosea, I. V., Benner, P., & Sundmacher, K.Learning reduced-order models for dynamic CO2 methanation using operator inferencePresented at: ESCAPE-34Florence, Italy, June 2, 2024.

Peterson, L., Goyal, P. K., Pontes Duff, I., Gosea, I. V., Bremer, J., Benner, P., & Sundmacher, K.Stability-Guaranteed Inference of Reduced-Order Models with Control of Power-to-X ProcessesPresented at: 2024 AIChE Annual MeetingSan Diego, USA, October 27, 2024.

Zimmermann, R. T., Geschke, A., Peterson, L., Bremer, J., & Sundmacher, K.A Smart Catalytic Fixed-Bed Reactor for CO2 MethanationPresented at: Achema 2024 Frankfurt, Germany, June 10, 2024.

Peterson, L., Bremer, J., Goyal, P. K., Gosea, I. V., Benner, P., & Sundmacher, K.Learning reduced-order models for dynamic CO2 methanation using operator inferencePresented at: ESCAPE34 - PSE24Florence, Italy, June 2, 2024.

Peterson, L., Bremer, J., & Sundmacher, K.Hybrid modeling of the catalytic CO2 methanation using process data and mechanistic knowledgePresented at: ReactEng23: Annual Meeting on Reaction Engineering 2023Frankfurt am Main, May 15, 2023.

Peterson, L., Sanchez Medina, E. I., Khalid, M. M., & Sundmacher, K.Surrogate modeling of dynamical systems: deep learning or model-order reduction?Presented at: ECML 2024 (ML4CCE workshop)Vilnius, Lithuania, September 9, 2024.

Peterson, L., Bremer, J., & Sundmacher, K.Hybrid modeling of the catalytic CO2 methanation using process data and mechanistic knowledgePresented at: ESCAPE-33Athens, Greece, June 18, 2023.

Peterson, L. (2020)Power-to-Methane: Derivation of a microkinetic model for the CO2 methanation reactionMaster's Thesis, Magdeburg: Otto-von-Guericke-Universität.

Peterson, L. (2018)Einfluss der Bacteriorhodopsin Orientierung auf die lichtgetriebene ATP-Produktion in bR-EF0F1-ProteoliposomenBachelor Thesis, Otto-von-Guericke-Universität, Magdeburg.

Peterson, L., Forootani, A., Sanchez Medina, E. I., Gosea, I. V., Sundmacher, K., & Benner, P. (2024)Towards Digital Twins for Power-to-X: Comparing Surrogate Models for a Catalytic CO2 Methanation ReactorTechRxivdoi: 10.36227/techrxiv.172263007.76668955/v1 .