Thermal Model of Cylindrical and Prismatic Lithium-Ion Cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Oven exposure testing is a standard benchmark that Li-ion cells must pass in order to be approved for sale by regulating bodies. In order to test the safety of new cell designs or electrode materials, manufacturers must make small test batches of cells. This can be both costly and time consuming. Using reaction kinetics that have been developed for electrode materials with electrolyte exposed to high temperature, and thermal properties of cells from the literature, a predictive model for oven exposure testing has been developed. The model predictions are compared to oven exposure test results for E-One/Moli Energy, Canada, 18650 /graphite cells and shown to be in good agreement. The model can predict the response of new cell sizes and electrode materials to oven exposure testing without actually producing any cells. This is illustrated with a number of examples: (i) increasing the specific surface area of the graphite electrode; (ii) using or other cathode substitutes instead of ; (iii) varying the diameter of cylindrical cells; and (iv) varying the thickness of prismatic cells. © 2001 The Electrochemical Society. All rights reserved.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it