A Study on the Effect of Porosity and Particles Size Distribution on Li-Ion Battery Performance
Bibliographic record
Abstract
A pseudo two-dimensional model (P2D) is presented that describes the effect of the structural properties of the positive electrode on Li-ion cell performance during discharge. The validation of the mono-modal model was done by using Doyle's experiment and results [C.M. Doyle, University of California, Berkeley (1995)]. A large increase or decrease in the porosity beyond a specific value led to a sharp change in the cell voltage curve and lower cell capacities. The maximum specific energy was obtained in the porosity range of 0.55, while the specific power still had a high value. Furthermore, different particle size distribution models, including mono-modal, bi-modal and 3-particle models, were compared to each other. The mono-modal model was the ideal state with the lowest total polarization. The bi-modal and 3-particle models approached this ideal state when the volume fraction of the smallest particles in their structures increased. This structural arrangement in these models led to more uniform local current density distribution profiles resulting in a greater decrease in cell polarization. Different discharge current densities were applied to different particle size distribution models, and the results showed that the particle size distribution has a greater effect at higher discharge current densities.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".