Gast ::
| Hauptseite > Publikationsdatenbank > Combining Lattice Boltzmann Simulation and Synchrotron Imaging to Study Bubble Dynamics in Electrodes of Vanadium Redox Flow Batte |
| Hauptseite > Publikationsdatenbank > Combining Lattice Boltzmann Simulation and Synchrotron Imaging to Study Bubble Dynamics in Electrodes of Vanadium Redox Flow Batte |
| Book/Dissertation / PhD Thesis | FZJ-2026-02773 |
2026
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag
Jülich
ISBN: 978-3-95806-955-8
This record in other databases:
Please use a persistent id in citations: urn:nbn:de:0001-2608101539132.015472450236 doi:10.34734/FZJ-2026-02773
Abstract: The large-scale integration of renewably generated electrical energy into power grids poses a formidable challenge due to its intermittent and spatially distributed nature. While traditional power systems rely on coal or gas-fired plants for load balancing and frequency regulation,the increasing penetration of renewable sources necessitates advanced energy storage solutions to bridge the gap between fluctuating supply and real-time demand. Vanadium redox flow batteries (VRFBs) have emerged as a promising durable energy storage technology, playing a crucial role in stabilizing renewable energy input, enabling seasonal energy storage, and enhancing overall grid flexibility. However, despite their advantages, VRFBs face critical performance limitations due to side reactions that occur at the electrodes. Among them, the hydrogen evolution reaction (HER) has been identified as a major source of efficiency losses, leading to an imbalance in state of charge, and bubble formation, which disrupts ion transport and reduces the effective reaction area within the electrode. Understanding the mechanistic details of gas evolution and its interaction with the porous electrode structure is therefore essential for further optimizing battery performance. To investigate gas evolution behavior in VRFB electrodes, synchrotron X-ray tomography was employed to obtain high-resolution three-dimensional images of gas bubbles formed during HER. These measurements enable a direct spatial characterization of individual bubbles and their morphology, but due to imaging contrast limitations, the electrode fibers could not be directly visualized in the presence of the electrolyte. To systematically analyze the observed bubble structures, we have developed a deep learning-based image processing framework, which enables automated segmentation, 3D reconstruction, and quantitative morphological analysis of bubbles. This approach facilitates high-throughput statistical evaluation of bubble size, shape, and spatial distribution under different electrochemical conditions. The results have revealed that increasingly negative electrode potentials intensify HER, producing larger and more irregular bubbles that accumulate in regions like the electrode borders, leading to pathway blockage and a reduced reaction area. However, the simultaneous visualization of bubbles and the underlying porous electrode microstructure could not be achieved in these experiments. To bridge this gap, additional synchrotron X-ray scans of dry electrodes were conducted, allowing for a more detailed characterization of the fiber structure. These structural insights were then incorporated into Lattice Boltzmann method (LBM) simulations, enabling a systematic investigation of how electrolyte flow, electrode compression, and HER rate influence bubble transport and retention within the porous network. The numerical simulations revealed that optimal electrolyte velocity enhances bubble removal, whereas excessive compression leads to gas entrapment, severely impairing mass transport. By correlating these results with experimental observations, this study provides a mechanistic understanding of how gas evolution influences mass transport and electrochemical performance in VRFBs. This work establishes a multi-scale framework limited to electrode- and pore-scale phenomena for investigating gas evolution in electrochemical energy storage systems, combining highresolution imaging, machine learning-based data analysis, and mesoscale numerical modeling. The methodologies developed in this dissertation advance the understanding of HERdriven bubble dynamics and lay the foundation for future research on multiphase phenomena in energy storage and conversion systems. By systematically addressing the interplay between electrochemical reactions, gas evolution, and electrode microstructure, this study provides new insights for optimizing electrode design and operational strategies, ultimately paving the way for more efficient and durable VRFBs, which are essential for the large-scale deployment of a renewable energy infrastructure.
; 
|
The record appears in these collections: |
PDF
Fulltext by OpenAccess repository