The Effect of Different Li(Ni<sub>1-x-y</sub>Mn<sub>x</sub>Co<sub>y</sub>)O<sub>2</sub>Positive Electrode Materials and Coatings on Parasitic Heat Flow as Measured by Isothermal Microcalorimetry, Ultra-High Precision Coulometry and Long Term Cycling
Bibliographic record
Abstract
Isothermal microcalorimetry is used to investigate the effect of different Li(Ni 1-x-y Mn x Co y )O 2 materials (NMC442, NMC532, NMC622) and coatings (Al 2 O 3 and a proprietary high voltage coating) on parasitic reactions that occur in Li-ion pouch type cells. NMC/graphite pouch cells were prepared with a typical organic carbonate - based electrolyte containing a well-known additive blend and were tested up to 4.4 V at 40°C. A new method of extracting the parasitic heat flow during both charge and discharge is introduced. Differences between charge and discharge parasitic heat flow yielded more insight into the behavior of high voltage parasitic reactions. Ultra-high precision coulometry, long-term charge discharge cycling, in-situ gas measurements, and electrochemical impedance spectroscopy were also used to compare the observed heat flow to well-known performance metrics. All coated cell types performed significantly better than uncoated NMC442/graphite cells. It was found that the magnitude of the parasitic heat flows did not correlate as expected to the precision coulometry results nor to the long term cycling results. In particular, cells with Al 2 O 3 -coated NMC622 had the highest parasitic heat flow among the cells with coated electrodes but competed for best performance in the cycling tests. The possible reasons for this unexpected result are explored.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".