Regensburg 2022 – wissenschaftliches Programm

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CPP: Fachverband Chemische Physik und Polymerphysik

CPP 14: Emerging Topics in Chemical and Polymer Physics, New Instruments and Methods

CPP 14.5: Vortrag

Dienstag, 6. September 2022, 10:30–10:45, H39

Transport of organic volatiles through paper: physics-informed neural networks for solving inverse and forward problems — •Alexandra Serebrennikova^{1, 4}, Raimund Teubler^{2, 4}, Lisa Hoffellner^{2, 4}, Erich Leitner^{2, 4}, Ulrich Hirn^{3, 4}, and Karin Zojer^{1, 4} — ¹Institute of Solid State Physics, TU Graz, Petersgasse 16, Graz, 8010, Austria — ²Institute of Analytical Chemistry and Food Chemistry, TU Graz, Stremayrgasse 9/II, Graz, 8010, Austria — ³Institute of Bioproducts and Paper Technology, TU Graz, Inffeldgasse 23, Graz, 8010, Austria — ⁴Christian Doppler Laboratory for mass transport through paper, Petersgasse 16, Graz, 8010, Austria

Transport of volatile organic compounds (VOCs) through porous media with active surfaces takes place in many applications, e.g., in cellulose-based materials for packaging. To date, mathematical models proposed in literature for this complex process are scarce and have not been systematically compiled together with experimental data.

Based on a model for water-vapor transport through paper (Ramarao et al. (2003)), we propose to describe transport of VOCs via diffusion in pores and sorption to fibers. It is key to determine the necessary material parameters for the model. Using experiments for that is challenging, as the related system of non-linear PDEs does not offer analytical solutions.

We demonstrate for dimethyl sulfoxide and n-tetradecane, how combining experimental concentration data with physics-informed neural networks yields these parameters as solution of an inverse problem.