Erlangen 2026 – wissenschaftliches Programm

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P: Fachverband Plasmaphysik

P 16: Poster Session Plasma Physics

P 16.60: Poster

Donnerstag, 19. März 2026, 13:45–15:45, Redoutensaal

CO₂-to-CO conversion in a micro cavity dielectric barrier discharge and initial data-driven analysis — •Michael Roloff, Henrik van Impel, David Eiselt, Volker Schulz-von der Gathen, Marc Böke, and Judith Golda — PIP, Ruhr-University Bochum, D-44801 Bochum

The micro cavity plasma array (MCPA) is an atmospheric pressure dielectric barrier discharge [1]. It serves as a research reactor to investigate ways of improving conversion by adding a catalyst. Fourier-transform infrared spectroscopy quantifies CO₂-to-CO conversion under different conditions. We present experiments using 1 slm helium with 0. 1 % CO₂ and up to 2 W power, yielding conversion rates of 15. 5 % (no catalyst), 14. 5 % (SrTiO₃), and 12 % (BaTiO₃). Additionally, the gas flow pattern were optimized in order to increase conversion efficiency.

A second separately aspect of the project covers data-driven methods to extract useful information from plasma diagnostics. In first tests, we applied neural networks and simple statistical tools to measured signals (e.g. current or spectra) to understand method behavior and interpret basic plasma characteristics.

The experiments and data-driven analysis are intended to be combined in the future to enable machine learning-based parameter estimation.

Supported by DFG within project A6 (SFB 1316)

[1] Dzikowski et al. 2020 Plasma Sources Sci. Technol. 29 035028

Keywords: Micro Cavity Plasma Array; CO2 Conversion; Dielectric Barrier Discharge; Data-driven Plasma Diagnostics; Machine Learning