Ternary Electrolyte Additive Mixtures for Li-Ion Cells that Promote Long Lifetime and Less Reactivity with Charged Electrodes at Elevated Temperatures
Bibliographic record
Abstract
Li[Ni1/3Mn1/3Co1/3]O2 (NMC111)/graphite and Li[Ni0.42Mn0.42Co0.16]O2 (NMC442)/graphite pouch cells demonstrate superb performance when ternary blends of electrolyte additives are added to the cells. These ternary blends contain one of vinylene carbonate (VC) or prop-1-ene-1,3-sultone (PES) plus a sulfur containing molecule and tris(trimethylsilyl) phosphite (TTSPi). Here, the excellent charge-discharge capacity retention of cells containing these ternary blends of additives is demonstrated at both 45°C and 55°C by comparison to cells with only VC or PES additives alone. The impact of a number of sulfur- and phosphorous-containing electrolyte additives on the reactivity of charged electrode materials with electrolyte at elevated temperatures was studied using accelerating rate calorimetry (ARC). The electrolyte additives, methylene methanedisulfonate (MMDS) and TTSPi, dramatically reduce the reactivity between lithiated (charged) graphite and electrolyte. The ternary electrolyte blends of VC + MMDS + TTSPi and PES + MMDS + TTSPi show no reactivity between charged graphite and electrolyte to above 200°C. By contrast, electrolytes with no additives or with PES alone show significant reactivity with lithiated graphite below 200°C. NMC/graphite cells with VC + MMDS + TTSPi or PES + MMDS + TTPSi additives will demonstrate long life and excellent safety.
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.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".