Studies of the Effect of High Voltage on the Impedance and Cycling Performance of Li[Ni<sub>0.4</sub>Mn<sub>0.4</sub>Co<sub>0.2</sub>]O<sub>2</sub>/Graphite Lithium-Ion Pouch Cells
Bibliographic record
Abstract
Li[Ni 0.4 Mn 0.4 Co 0.2 ]O 2 (NMC442)/graphite pouch cells containing various electrolyte additives, either singly or in combination, were studied using cycling experiments up to 4.4 and 4.5 V coupled with simultaneous electrochemical impedance spectroscopy (EIS) measurements. The impedance of most cells increased dramatically at 4.4 and 4.5 V, but was nearly reversible over one cycle. However, during continued cycling, the impedance of all cells slowly increased at all potentials. Electrolyte additives were found to dramatically affect this behavior. The impacts of adding prop-1-ene-1,3-sultone (PES), vinylene carbonate (VC), triallyl phosphate (TAP), methylene methane disulfonate (MMDS), ethylene sulfate (DTD) and/or tris(-trimethyl-silyl)-phosphite (TTSPi) to 1M LiPF 6 ethylene carbonate:ethyl methyl carbonate (EC:EMC) electrolyte were studied. PES-containing cells had dramatically lower impedance and better capacity retention than VC and TAP-containing cells during both 4.4 and 4.5 V experiments. When MMDS, DTD and/or TTSPi were added in combination with PES, the performance was improved further. Finally, continuous charge-discharge cycling was compared to cycling with a 24-hour hold applied at the top of charge at 4.4 V. The high voltage hold led to severe impedance growth which could be partially overcome through the use of optimal additive combinations.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".