Study of Electrolyte and Electrode Composition Changes vs Time in Aged Li-Ion Cells
Bibliographic record
Abstract
Many studies of Li-ion cells examine compositional changes to electrolyte and electrodes to determine desirable or undesirable reactions that affect cell performance. Cells involved in these studies typically have a limited test lifetime due to the resource intensive and time-consuming nature of these experiments. Here, electrolyte and electrode analyses were performed on a large matrix of cells tested at various conditions and with various cycle lifetimes. The matrix included LiNi0.5Mn0.3Co0.2O2 (NMC532)/graphite and LiNi0.6Mn0.2Co0.2O2 (NMC622)/graphite pouch cells with excellent performing electrolyte mixtures, both cycling and storage protocols at 40 °C and 55 °C with both 4.3 V and 4.4 V upper cutoff potentials. This study presents post-test analysis (electrochemical impedance spectroscopy, differential voltage analysis, differential thermal analysis), electrolyte analysis (gas chromatography, quantitative nuclear magnetic resonance), and electrode analysis (micro X-ray fluorescence) for these cells after 3, 6, 9, and 12 months of testing. Many products and reactants, such as fraction of transesterification, gas production, transition metal dissolution appeared to have a constant rate of increase in this 12-month observation period. In most cases, results from cells after 3 to 6 months of testing could be used to reasonably estimate the status of the cells (electrolyte composition, gas production, transition metal dissolution) at 12 months.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".