Ion–Dipole-Interaction-Induced Encapsulation of Free Residual Solvent for Long-Cycle Solid-State Lithium Metal Batteries
Bibliographic record
Abstract
Owing to high ionic conductivity and mechanical strength, poly(vinylidene fluoride) (PVDF) electrolytes have attracted increasing attention for solid-state lithium batteries, but highly reactive residual solvents severely plague cycling stability. Herein, we report a free-solvent-capturing strategy triggered by reinforced ion–dipole interactions between Li + and residual solvent molecules. Lithium difluoro(oxalato)borate (LiDFOB) salt additive with electron-withdrawing capability serves as a redistributor of the Li + electropositive state, which offers more binding sites for residual solvents. Benefiting from the modified coordination environment, the kinetically stable anion-derived interphases are preferentially formed, effectively mitigating the interfacial side reactions between the electrodes and electrolytes. As a result, the assembled solid-state battery shows a lifetime of over 2000 cycles with an average Coulombic efficiency of 99.9% and capacity retention of 80%. Our discovery sheds fresh light on the targeted regulation of the reactive residual solvent to extend the cycle life of solid-state batteries.
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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".