@article{GumpertJanssenBrabecetal.2023, author = {Gumpert, Fabian and Janßen, Annika and Brabec, Christoph J. and Egelhaaf, Hans-Joachim and Lohbreier, Jan and Distler, Andreas}, title = {Predicting layer thicknesses by numerical simulation for meniscus-guided coating of organic photovoltaics}, series = {Engineering Applications of Computational Fluid Mechanics}, volume = {17}, journal = {Engineering Applications of Computational Fluid Mechanics}, number = {1}, publisher = {Informa UK Limited}, issn = {1994-2060}, doi = {10.1080/19942060.2023.2242455}, year = {2023}, abstract = {To achieve maximum efficiency in organic photovoltaics (OPV), functional layers with uniform and exactly predefined thickness are required. An in-depth understanding of the coating process is therefore crucial for an accurate process control. In this paper, the meniscus-guided blade coating process, which is the most commonly used process for the manufacturing of organic electronics, is investigated by experimental and numerical methods. A computational fluid dynamics (CFD) model is created to simulate the coating behaviour of P3HT:O IDTBR, an industrial state-of-the-art active material system used in OPV, and its results' independence of numerical parameters is ensured. In particular, the influence of the coating velocity and the initially injected fluid volume on the resulting wet film thickness is studied. The developed CFD analysis is able to reproduce the experimental results with very high accuracy. It is found that the film thickness follows a power law dependence on the velocity (˜v 2/3) and a linear dependence on the ink volume (˜V). Accordingly, an analytical expression based on our theoretical considerations is presented, which predicts the wet film thickness as a function of the coating velocity and the ink volume only based on easily accessible ink properties. Consequently, this CFD model can effectively substitute time-consuming and expensive experiments, which currently have to be performed manually in the laboratory for a multitude of novel material systems, and thus supports highly accelerated material research. Moreover, the results of this work can be used to achieve homogeneous large-area coatings by utilising accelerated blade coating.}, language = {en} } @article{BasuGumpertLohbreieretal.2024, author = {Basu, Robin and Gumpert, Fabian and Lohbreier, Jan and Morin, Pierre-Olivier and Vohra, Varun and Liu, Yang and Zhou, Yinhua and Brabec, Christoph J. and Egelhaaf, Hans-Joachim and Distler, Andreas}, title = {Large-area organic photovoltaic modules with 14.5\% certified world record efficiency}, series = {Joule}, volume = {8}, journal = {Joule}, number = {4}, publisher = {Elsevier BV}, issn = {2542-4351}, doi = {10.1016/j.joule.2024.02.016}, pages = {970 -- 978}, year = {2024}, abstract = {Organic photovoltaics (OPVs) have experienced a significant increase in power conversion efficiency (PCE) recently, now approaching 20\% on small-cell level. Since the efficiencies on the module level are still substantially lower, focused upscaling research is necessary to reduce the gap between cells and modules. In this work, we present the upscaling of PM6:Y6-C12:PC 61 BM-based devices, processed in ambient air from non-halogenated solvents, from small-area cells to large-area modules with barely any performance loss. Supported by computational fluid dynamics simulations, an acceler- ated blade coating process that enables homogeneous coatings with <5\% thickness deviation over 200 cm 2 is developed. Additional finite element method simulations are used to optimize the module layout and minimize the inevitable losses caused by electrode resistances and inactive interconnect areas to 1.9\% and 3.5\%, respectively. Finally, a 204-cm 2 OPV module with a certified PCE of 14.5\% (15.0\% on active area) is fabricated, which constitutes the new world record.}, language = {en} } @article{GumpertJanssenBasuetal.2024, author = {Gumpert, Fabian and Janßen, Annika and Basu, Robin and Brabec, Christoph J. and Egelhaaf, Hans-Joachim and Lohbreier, Jan and Distler, Andreas}, title = {On the theoretical framework for meniscus-guided manufacturing of large-area OPV modules}, series = {Progress in Organic Coatings}, volume = {192}, journal = {Progress in Organic Coatings}, publisher = {Elsevier BV}, issn = {0300-9440}, doi = {10.1016/j.porgcoat.2024.108505}, pages = {10}, year = {2024}, abstract = {Although the formation of plasma electrolytic oxidation (PEO) coatings on aluminum alloys can significantly enhance their service life, they may still suffer from corrosion damage when exposed to harsh environments with strong corrosivity for a long time. In this work, chitosan (CS) was dissolved in four acids, i.e. hydrochloric acid (HCl), citric acid (CA), lactic acid (LA), and acetic acid (HAc), and deposited onto the PEO-coated 5052 aluminum alloy using dip coating method. Scanning electron microscope (SEM), energy dispersive spectrometer (EDS), atomic force microscope (AFM), contact angle (CA) meter, grazing incidence X-ray diffraction (GIXRD), Fourier transform infrared spectrometer (FTIR), and electrochemical workstation system were used to explore the enhancement of the corrosion resistance of PEO-coated 5052 aluminum alloy by application of CS film prepared in different solvent acids. The results showed that the interactions between chitosan and acid ions affects the uniformity, hydrophobicity, thickness and surface roughness of the CS/PEO coating. The HAc-CS/PEO coating had the lowest surface roughness of 32.4 ± 3.9 nm, the largest contact angle of 85.7 ± 2.0◦, and the thickest CS film of 20 μm, which significantly improved corrosion resistance of PEO-coated aluminum alloy.}, language = {en} } @inproceedings{GumpertVamboltSchmidtetal.2024, author = {Gumpert, Fabian and Vambolt, Eugen and Schmidt, Michael and Fromme, Lars and Dietz, Armin and Lohbreier, Jan}, title = {Physics-Informed Neural Networks to predict the Power Transmission of Electric Road Systems}, series = {2024 1st International Conference on Production Technologies and Systems for E-Mobility (EPTS)}, booktitle = {2024 1st International Conference on Production Technologies and Systems for E-Mobility (EPTS)}, publisher = {IEEE}, doi = {10.1109/EPTS61482.2024.10586741}, pages = {1 -- 7}, year = {2024}, language = {en} } @article{GumpertEitelKottasetal.2025, author = {Gumpert, Fabian and Eitel, Dominik and Kottas, Olaf and Helbig, Uta and Lohbreier, Jan}, title = {Multiscale simulations of three-dimensional nanotube networks: Enhanced modeling using unit cells}, series = {Computational Materials Science}, volume = {254}, journal = {Computational Materials Science}, publisher = {Elsevier BV}, issn = {0927-0256}, doi = {10.1016/j.commatsci.2025.113891}, year = {2025}, abstract = {This study presents a simulation approach for three-dimensional nanotube networks using cubic and tetragonal unit cells to enhance modeling efficiency. A random-walk algorithm was developed to generate these networks, which were analyzed using a Finite Element Method (FEM) simulation to assess their electrical conductivity. The percolation probability as a function of the nanotube filling factor can be derived from these simulation results. Smaller tetragonal unit cells can replicate the behavior of larger networks with significantly reduced computational effort, achieving up to a 20-fold reduction in computation time while obtaining similar results. In this work, the focus is on carbon-doped titanate nanotubes for hydrogen applications, but the method is adaptable to other applications with similar nanotube network composites. The findings are expected to provide a universal framework for the investigation of nanotube-based materials.}, language = {en} }