Methyl Acetate as a Co-Solvent in NMC532/Graphite Cells
Bibliographic record
Abstract
One goal of researchers focusing on lithium-ion batteries for electric vehicles is to decrease the time required for charging. This can be done by several methods, including increasing the electrolyte transport properties. Methyl acetate, used as a co-solvent in the electrolyte, has been shown by a number of researchers to increase cell rate capability dramatically but careful considerations of the impact of methyl acetate on cell lifetime have not been published to our knowledge. The impacts of methyl acetate as a co-solvent in NMC532/ graphite cells were systematically studied in this work. Ex-situ gas evolution measurements, electrochemical impedance spectroscopy, high rate charging tests, ultra-high precision coulometry, isothermal microcalorimetry and long term cycling at both 20 and 40°C were used to probe the impacts of including methyl acetate as a co-solvent. This work will be of great interest to Li-ion battery scientists developing cells that can support rapid charge and still maintain long lifetime.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".