Structure‐Tunable Fluorinated Polyester Electrolytes with Enhanced Interfacial Stability for Recyclable Solid‐State Lithium Metal Batteries
Bibliographic record
Abstract
Polyesters, with their tunable chemical structures and environmental sustainability, have drawn growing attention as solid polymer electrolytes for next-generation solid-state lithium metal batteries (SSLMBs). Through a comprehensive experimental and theoretical study involving the systematic variation of carbon chain lengths in the flexible (diol) and coordinating (diacid) segments, along with selective fluorination at distinct positions along the polymer backbone, 18 types of polyester are fabricated and demonstrate that fluorination at the coordinating segment significantly enhances ionic conductivity by suppressing crystallinity. In contrast, fluorination at the flexible segment reduces ionic migration barriers by providing more homogeneous coordinating sites, thereby improving the lithium-ion transference number, despite increasing chain rigidity and a reduction in overall ionic conductivity. The optimized fluorinated polyesters exhibit excellent interfacial stability with lithium metal by facilitating the formation of a LiF-rich solid electrolyte interphase, as supported by experimental and theoretical simulation analysis. More importantly, to enhance cost-effectiveness and sustainability, a solvent-based recycling route has been developed, achieving substantial recovery yields and notable environmental benefits. This work provides a versatile molecular design and closed-loop recovery strategy for fluorinated polyester electrolytes, advancing their practical application in high-energy and sustainable SSLMBs.
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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 | 0.000 | 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".