Exploring the Impact of Electrode Microstructure on Redox Flow Battery Performance Using a Multiphysics Pore Network Model
Why this work is in the frame
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Bibliographic record
Abstract
The redox flow battery is a promising energy storage technology for managing the inherent uncertainty of renewable energy sources. At present, however, they are too expensive and thus economically unattractive. Optimizing flow batteries is thus an active area of research, with the aim of reducing cost by maximizing performance. This work addresses microstructural electrode optimizations by providing a modeling framework based on pore-networks to study the multiphysics involved in a flow battery, with a specific focus on pore-scale structure and its impact on transport processes. The proposed pore network approach was extremely cheap in computation cost (compared to direct numerical simulation) and therefore was used for parametric sweeps to search for optimum electrode structures in a reasonable time. It was found that that increasing porosity generally helps performance by increasing the permeability and flow rate at a given pressure drop, despite reducing reactive surface area per unit volume. As a more nuanced structural study, it was found that aligning fibers in the direction of flow helps performance by increasing permeability but showed diminishing returns beyond slight alignment. The proposed model was demonstrated in the context of a hydrogen bromine flow battery but could be applied to any system of interest.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it