Prof. Dr.-Ing. Jan Trieschmann
I am junior professor and head of Theoretical Electrical Engineering at Kiel University. Our research focus is on computational electromagnetics and physics-informed data-driven modeling in the subject areas of electromagnetic systems, plasma engineering, physical electronics, materials science, and photonics.
Specifically, this relates to
- the numerical modeling of the dynamics and the electromagnetic response of tunable periodic (plasma) band gap structures and RF devices, and
- the multi-scale / multi-physics model coupling of the plasma-surface interface.
These topics are addressed using conventional numerical methods (e.g., Finite Difference, Finite Element, and Finite Volume techniques) as well as data-driven methods such as surrogate models and artificial neural networks. The latter involves machine learning algorithms to realize the bridging, for instance, of the atomistic surface dynamics scale and the macroscopic scale of the gas-phase in plasma modeling.
Team
Tobias Gergs, M.Sc.
Ihda Chaerony Siffa, M.Sc. (external PhD student, INP Greifswald)
Luca Vialetto, Ph.D.
Christian Stüwe, B.Sc.
Former Members
Borislav Borislavov, M.Sc.
Florian Krüger, M.Sc.
Frederik Schmidt, Dr.-Ing.
Projects
Deutsche Forschungsgemeinschaft – GEPRIS
Ongoing projects
Collaborative Research Centre 1461 – Neurotronics: Bio-inspired Information Pathways
CRC 1461 / Project C05 – Multiscale transport modeling: From process plasmas to resistive switching devices
funded by Deutsche Forschungsgemeinschaft (2021-2024)
Finished projects
Transregio 87 – Pulsed high power plasmas for the synthesis of nanostructured functional layers
TRR 87 / Project C08 – Heavy particle processes in high power plasmas
funded by Deutsche Forschungsgemeinschaft (2018-2022)
Publications
List of publications
arXiv preprints
Dissertation: Particle transport in technological plasmas
Selected Publications
- T. Gergs, T. Mussenbrock & J. Trieschmann. Physics-separating artificial neural networks for predicting sputtering and thin film deposition of AlN in Ar/N2 discharges on experimental timescales. Journal of Physics D: Applied Physics 56, 194001 (2023)
- T. Gergs, T. Mussenbrock & J. Trieschmann. Charge-optimized many-body interaction potential for AlN revisited to explore plasma–surface interactions. Scientific Reports 13, 5287 (2023)
- T. Gergs, T. Mussenbrock & J. Trieschmann. 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, 084003 (2023)
- I. Adamovich, S. Agarwal, E. Ahedo, L.L. Alves, S. Baalrud, N. Babaeva, A. Bogaerts, A. Bourdon, P.J. Bruggeman, C. Canal, E.H. Choi, S. Coulombe, Z. Donkó, D.B. Graves, S. Hamaguchi, D. Hegemann, M. Hori, H.-H. Kim, G.M.W. Kroesen, M.J. Kushner, A. Laricchiuta, X. Li, T.E. Magin, S.M. Thagard, V. Miller, A.B. Murphy, G.S. Oehrlein, N. Puac, R.M. Sankaran, S. Samukawa, M. Shiratani, M. Šimek, N. Tarasenko, K. Terashima, E.T. Jr, J. Trieschmann, S. Tsikata, M.M. Turner, I.J. van der Walt, M.C.M. van de Sanden, and T. von Woedtke. The 2022 Plasma Roadmap: low temperature plasma science and technology. Journal of Physics D: Applied Physics 55, 373001 (2022).
- S. Yarragolla, T. Hemke, J. Trieschmann, F. Zahari, H. Kohlstedt, and T. Mussenbrock. Stochastic behavior of an interface-based memristive device. Journal of Applied Physics 131, 134304 (2022).
- T. Gergs, B. Borislavov, J. Trieschmann. Efficient Plasma-Surface Interaction Surrogate Model for Sputtering Processes Based on Autoencoder Neural Networks. Journal of Vacuum Science & Technology B 40, 012802 (2022).
- T. Gergs, F. Schmidt, T. Mussenbrock, J. Trieschmann. Generalized method for charge transfer equilibration in reactive molecular dynamics. Journal of Chemical Theory and Computation. Journal of Chemical Theory and Computation 17, 6691 (2021).
- J. Trieschmann, A. W. Larsen, T. Mussenbrock, S. B. Korsholm. Kinetic simulation of electron cyclotron resonance assisted gas breakdown in split-biased waveguides for ITER collective Thomson scattering diagnostic. Physics of Plasmas 28, 082505 (2021).
- S. Wilczek, J. Schulze, R. P. Brinkmann, Z. Donkó, J. Trieschmann, T. Mussenbrock. Electron dynamics in capacitively coupled radio frequency discharges. Journal of Applied Physics 127, 181101 (2021).
- F. Zahari, F. Schlichting, J. Strobel, S. Dirkmann, J. Cipo, S. Gauter, J. Trieschmann, R. Marquardt, G. Haberfehlner, G. Kothleitner, L. Kienle, T. Mussenbrock, M. Ziegler, H. Kersten, H. Kohlstedt. Correlation between sputter deposition parameters and I-V characteristics in double-barrier memristive devices. Journal of Vacuum Science & Technology B 37, 061203 (2019).
- F. Krüger, T. Gergs, J. Trieschmann. Machine learning plasma-surface interface for coupling sputtering and gas-phase transport simulations. Plasma Sources Science and Technology 28, 035002 (2019).
- F. Schmidt, T. Mussenbrock, J. Trieschmann. Consistent simulation of capacitive radio-frequency discharges and external matching networks. Plasma Sources Science and Technology 27, 105017 (2018).
- J. Trieschmann, T. Mussenbrock. Kinetic bandgap analysis of plasma photonic crystals. Journal of Applied Physics 124, 173302 (2018).
- S. Dirkmann, M. Ziegler, M. Hansen, H. Kohlstedt, J. Trieschmann, T. Mussenbrock. Kinetic simulation of filament growth dynamics in memristive electrochemical metallization devices. Journal of Applied Physics 118, 214501 (2015).
- J. Trieschmann, T. Mussenbrock. Transport of sputtered particles in capacitive sputter sources. Journal of Applied Physics 118, 033302 (2015).
Teaching
Lecture notes and YouTube channels
Links
Theoretische Elektrotechnik @ CAU Kiel
ORCID iD: 0000-0001-9136-8019
ResearcherID: O-7549-2014
Scopus: 48762047100
Google Scholar profile
LinkedIn profile
Contact
Prof. Dr.-Ing. Jan Trieschmann
Kiel University
Faculty of Engineering
Theoretical Electrical Engineering
Kaiserstraße 2
D-24143 Kiel
Germany
Phone
Office
+49 (0) 431 / 880 6357
KS4-1.004