Succinic Anhydride as an Enabler in Ethylene Carbonate-Free Linear Alkyl Carbonate Electrolytes for High Voltage Li-Ion Cells
Bibliographic record
Abstract
Ethylene carbonate-free electrolytes containing 1 M LiPF 6 in ethyl methyl carbonate with succinic anhydride as an enabler exhibited promising cycling and storage performance in Li(Ni 0.4 Mn 0.4 Co 0.2 )O 2 /graphite pouch type Li-ion cells tested to 4.5 V. Although cells using 1 M LiPF 6 in EMC can barely function due to the poor passivation of the graphite electrode, the addition of 1% succinic anhydride allows cells to operate well. Compared to other enablers such as vinylene carbonate, succinic anhydride provides similar cycling and storage performance at 40°C and improved storage or cycling performance at 60°C. Succinic anhydride also limits gas evolution, especially at high temperatures where cells with vinylene carbonate normally produces large amounts of gas. Symmetric cell studies showed that adding succinic anhydride to cells greatly increased the impedance of the graphite electrode after formation. However, the impedance of the graphite electrode decreased substantially during cycling, leading to a significant decrease of impedance in the full pouch cells. With succinic anhydride as an enabler, ethylene carbonate-free linear alkyl carbonate electrolytes may be suitable for high temperature applications in some Li-ion cells.
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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 | 0.001 |
| 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".