Designing Low‐Concentration Propylene Carbonate‐based Electrolyte by Manipulating Lithium<sup>+</sup>‐Solvation Structure for Graphite Anode
Bibliographic record
Abstract
Abstract We systematically study the correlation between Li + ‐solvation structure, interfacial stability, and electrochemical behavior in the system of graphite anode with low‐concentration (0.5 M) propylene carbonate (PC)‐based electrolyte (LCPE). 1,1,2,2‐tetrafluoroethyl‐2,2,3,3‐tetrafluoropropylether (TTE) [or 1,1,2,2‐tetrafluoroethyl‐2,2,2‐trifluoroethyl ether (HFE)] is used to manipulate the solvation structures of Li + in the LCPEs. Varying Li + ‐solvation structures are realized by changing the volume ratios of PC to TTE (or HFE) in the LCPEs. With the increase of TTE (or HFE) dosages, the relative contents of LiF and Li x PO y F z in SEI derived from increase, while the decomposition products of PC reduce. With enough TTE (or HFE) in the LCPE, the Li||graphite cell exhibits reversible (de)lithiation without PC co‐intercalation and continuous electrolyte decomposition due to the shield of a compact SEI rich in LiF and Li x PO y F z . Our work proves it is practicable to achieve LiF‐riched SEIs on graphite anodes and realize reversible (de)lithiation in LCPEs by regulating the Li + ‐solvation structures with inert cosolvents.
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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".