A Comparative Study of Pyridine-Boron Trifluoride, Pyrazine-(BF<sub>3</sub>)<sub>2</sub>and Triazine-(BF<sub>3</sub>)<sub>3</sub>as Electrolyte Additives for Lithium-Ion Cells
Bibliographic record
Abstract
The novel electrolyte additives pyridine boron trifluoride, pyrazine di-boron trifluoride and triazine tri-boron trifluoride were compared in Li[Ni 1/3 Mn 1/3 Co 1/3 ]O 2 /graphite and Li[Ni 0.42 Mn 0.42 Co 0.16 ]O 2 /graphite pouch cells. This series of additives allowed the Lewis base:BF 3 ratio to be systematically varied. The results were compared to baseline experiments on cells with well-known additives such as vinylene carbonate (VC) or prop-1-ene-1,3-sultone (PES). Increasing the BF 3 content on the additive can reduce the impedance of cells during charge-discharge cycling. However the coulombic efficiency, charge endpoint capacity slippage and long-term cycling behavior of these pouch cells was not improved by increasing the content of BF 3 in the additives.
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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 | 0.000 | 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".