Gas Evolution during Unwanted Lithium Plating in Li-Ion Cells with EC-Based or EC-Free Electrolytes
Bibliographic record
Abstract
Lithium plating can be induced in any Li-ion cell that has a graphite negative electrode by increasing the charge rate sufficiently at fixed temperature or by lowering the temperature at a fixed charge rate. Recently, ethylene carbonate (EC)-free electrolytes, such as 1 M LiPF 6 in 98% ethyl methyl carbonate (EMC): 2% vinylene carbonate (VC), have been shown to passivate lithiated graphite effectively and allow Li[Ni 0.42 Mn 0.42 Co 0.16 ]O 2 /graphite (NMC442/graphite) Li-ion cells to operate effectively for hundreds of charge discharge cycles. High charge rates and low temperatures were applied to Li[Ni 1/3 Mn 1/3 Co 1/3 ]O 2 /graphite (NMC111/graphite) pouch cells containing EC-free EMC-based electrolytes with additives to study unwanted lithium plating. In such electrolytes, the plated lithium metal is not well passivated and reacts to create gas while in the same cells with 1 M LiPF 6 EC:EMC (3:7) electrolyte no gas is observed when Li plating occurs because EC passivates metallic Li well. The volume of the pouch cells with EC-free electrolytes increased sharply when Li plating occurred as measured using in-situ methods. In cells having both EC-based and EC-free electrolytes, lithium plating was the cause of rapid capacity loss at high charge rates at both 10°C and 22°C.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".