Microporous Substrate Effect on SECM Steady State Current- A 3D Modeling Study Critical to Battery Electrode Performance
Bibliographic record
Abstract
Scanning electrochemical microscopy (SECM) enables the study of mass transport in porous substrates with microscale spatial resolution, which is profoundly influenced by the substrate’s architecture. Here, a 3D SECM modeling was used to compare the impact of substrate geometry on transport in three porous structures: a superposition (SP) and two high fidelity (HF-1 and HF-2) models. It was found that the steady-state current decreases with an increase in the geometric complexity from SP to HF-1 to HF-2, indicating the presence of more tortuous paths in HF-2. Despite having the same porosity and thickness values, the disparity between the SP and the two HF substrates shows the effect of microporous geometry. Our findings also demonstrated the deviation of all three substrates from Bruggeman’s predictions, which highlights the significance of modeling to rationalize the transport properties in commercial battery electrodes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".