Salt and Solvent Activities up to the Solvate Composition for LiPF <sub>6</sub> in Ethylene Carbonate and LiPF <sub>6</sub> in Dimethyl Carbonate
Bibliographic record
Abstract
The phase stability of liquid electrolytes for lithium-ion batteries is often a limiting factor for their operation, particularly under low temperature conditions and near the solubility limits. Despite the central role of the thermodynamic activities of nonaqueous electrolyte components in governing phase behavior, they generally remain poorly investigated in concentrated regimes. In the current work, we investigate concentrated electrolytes via the study of the thermodynamic activities of species in solution up to the first solid solvate composition for two binary lithium-ion battery carbonate electrolytes: LiPF 6 in ethylene carbonate and LiPF 6 in dimethyl carbonate. The enthalpies of fusion of the relevant solid solvates (EC) 4 LiPF 6 and (DMC) 3 LiPF 6 were measured to determine the activities of the species from reported solid–liquid equilibrium data up to the first solvate composition. For LiPF 6 in ethylene carbonate, we find that deviations from ideality continue to increase with concentration beyond the dilute limit up to 3.54 m . For LiPF 6 in dimethyl carbonate, we find that the salt activity coefficient continues to decrease beyond the dilute limit to moderate concentrations before increasing monotonically until the solvate composition. Our approach taken herein to use binary activity data in the study of liquidus lines and solution energetics will aid in the study of practical ternary Li-ion battery electrolytes, for which thermal stability is important but generally unresolved.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".