Low-Voltage Operation and Lithium Bis(fluorosulfonyl)imide Electrolyte Salt Enable Long Li-Ion Cell Lifetimes at 85 °C
Bibliographic record
Abstract
LiFePO4/graphite (LFP), Li[Ni0.5Mn0.3Co0.2]O2/graphite (NMC3.8 V, balanced for 3.8 V cut-off), and Li[Ni0.83Mn0.06Co0.11]O2/graphite (Ni83, balanced for 4.06 V cut-off) cells were tested at 85 °C. Three strategies were used to improve cell lifetime for all positive electrode materials at 85°C. First, low voltage operation (<4.0 V) was used to limit the parasitic reactions at the positive electrode. Second, LiFSI (lithium bis(trifluoromethanesulfonyl)imide) was used as the electrolyte salt for its superior thermal stability over LiPF6 (lithium hexafluorophosphate). The low voltage operation avoids the aluminum corrosion seen at higher voltages with LiFSI. NMC3.8 V cells were operated at 6 C charge and 6 C discharge without issue for 2500 cycles and then moved to room temperature where normal operation was obtained. Finally, dimethyl-2,5-dioxahexane carboxylate (DMOHC) was used as a sole electrolyte solvent or mixed with dimethyl carbonate. μ-XRF data showed no detectable levels of transition metal deposition on the negative electrode of Ni83 and LFP cells, and DMOHC cells showed less gassing after testing compared to EC-based electrolytes. We found incredible capacity retention and cycle life for Ni83 and NMC3.8 V cells using DMOHC and LiFSI at 70 °C and at 85 °C in tests that ran for more than 6 and 5 months (and are still running), respectively.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".