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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".