Dr.-Ing. Tobias Gergs

Trieschmann, J., Vialetto, L., & Gergs, T. (2023). Review: Machine learning for advancing low-temperature plasma modeling and simulation. Journal of Micro/Nanopatterning, Materials, and Metrology, 22(04). https://doi.org/10.1117/1.JMM.22.4.041504 Cite

De Los Arcos, T., Awakowicz, P., Böke, M., Boysen, N., Brinkmann, R. P., Dahlmann, R., Devi, A., Eremin, D., Franke, J., Gergs, T., Jenderny, J., Kemaneci, E., Kühne, T. D., Kusmierz, S., Mussenbrock, T., Rubner, J., Trieschmann, J., Wessling, M., Xie, X., … Grundmeier, G. (2023). PECVD and PEALD on polymer substrates (part II): Understanding and tuning of barrier and membrane properties of thin films. Plasma Processes and Polymers, e2300186. https://doi.org/10.1002/ppap.202300186 Cite

De Los Arcos, T., Awakowicz, P., Benedikt, J., Biskup, B., Böke, M., Boysen, N., Buschhaus, R., Dahlmann, R., Devi, A., Gergs, T., Jenderny, J., Von Keudell, A., Kühne, T. D., Kusmierz, S., Müller, H., Mussenbrock, T., Trieschmann, J., Zanders, D., Zysk, F., & Grundmeier, G. (2023). PECVD and PEALD on polymer substrates (part I): Fundamentals and analysis of plasma activation and thin film growth. Plasma Processes and Polymers, e2300150. https://doi.org/10.1002/ppap.202300150 Cite

Gergs, T., Mussenbrock, T., & Trieschmann, J. (2023). Physics-separating artificial neural networks for predicting sputtering and thin film deposition of AlN in Ar/N ₂ discharges on experimental timescales. Journal of Physics D: Applied Physics, 56(19), 194001. https://doi.org/10.1088/1361-6463/acc07e Cite

Gergs, T., Mussenbrock, T., & Trieschmann, J. (2023). Physics-separating artificial neural networks for predicting initial stages of Al sputtering and thin film deposition in Ar plasma discharges. Journal of Physics D: Applied Physics, 56(8), 084003. https://doi.org/10.1088/1361-6463/acb6a4 Cite

Gergs, T., Mussenbrock, T., & Trieschmann, J. (2023). Charge-optimized many-body interaction potential for AlN revisited to explore plasma–surface interactions. Scientific Reports, 13, 5287. https://doi.org/https://doi.org/10.1038/s41598-023-31862-8 Cite

Gergs, T., Mussenbrock, T., & Trieschmann, J. (2022). Molecular dynamics study on the role of Ar ions in the sputter deposition of Al thin films. Journal of Applied Physics, 132(6), 063302. https://doi.org/10.1063/5.0098040 Cite

Gergs, T., Monti, C., Gaiser, S., Amberg, M., Schütz, U., Mussenbrock, T., Trieschmann, J., Heuberger, M., & Hegemann, D. (2022). Nanoporous SiOx plasma polymer films as carrier for liquid‐infused surfaces. Plasma Processes and Polymers, 19(8), 2200049. https://doi.org/10.1002/ppap.202200049 Cite

Gergs, T., Borislavov, B., & Trieschmann, J. (2022). Efficient plasma-surface interaction surrogate model for sputtering processes based on autoencoder neural networks. Journal of Vacuum Science & Technology B, 40(1), 012802. https://doi.org/10.1116/6.0001485 Cite

Gergs, T., Schmidt, F., Mussenbrock, T., & Trieschmann, J. (2021). Generalized Method for Charge-Transfer Equilibration in Reactive Molecular Dynamics. Journal of Chemical Theory and Computation, 17(11), 6691–6704. https://doi.org/10.1021/acs.jctc.1c00382 Cite

Schmidt, F., Trieschmann, J., Gergs, T., & Mussenbrock, T. (2019). A generic method for equipping arbitrary rf discharge simulation frameworks with external lumped element circuits. Journal of Applied Physics, 125(17), 173106. https://doi.org/10.1063/1.5091965 Cite

Krüger, F., Gergs, T., & Trieschmann, J. (2019). Machine learning plasma-surface interface for coupling sputtering and gas-phase transport simulations. Plasma Sources Science and Technology, 28(3), 035002. https://doi.org/10.1088/1361-6595/ab0246 Cite

Gergs, T., Dirkmann, S., & Mussenbrock, T. (2018). Integration of external electric fields in molecular dynamics simulation models for resistive switching devices. Journal of Applied Physics, 123(24), 245301. https://doi.org/10.1063/1.5029877 Cite