Multiphysics Simulation of Multi-layered Fibrous Electrodes for the Vanadium Redox Flow Battery
Bibliographic record
Abstract
Electrospinning can create customized flow-through electrodes for redox flow batteries with small fibers to enhance reactive surface area. A downside is higher pressure drop and parasitic pumping losses. Multilayered electrodes are a promising remedy, but it is not obvious what properties each layer should have to get the most benefit. In this work, a multiphysics simulation was used to explore the impact of varying the properties of each layer on the performance of a cell, including fiber size, fiber alignment, and porosity. The results showed that a 300% increase in limiting current can be obtained over commercial materials when the layer near the membrane has larger fibers with smaller fibers in each successive layer (1.8, 1.0 & 0.2 um, respectively). This arrangement had relatively lower overall efficiency once pumping power was taken into account. A compromise was obtained by placing a high porosity layer near the membrane with lower porosity in each successive layer (91%, 86%, and 81%, respectively). This case resulted in a 250% increase in limiting current, while expending only 0.1% of the output power on pumping.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".