Uniform Liquid–Confined Copolymer Gel Enables Wide‐Temperature Lithium Metal Batteries (−20 to 90 °C)
Bibliographic record
Abstract
Abstract Gel polymer electrolytes (GPEs) promise to combine the high ionic conductivity of liquids with the mechanical robustness of solids for lithium metal batteries. However, temperature‐induced phase separation compromises interfacial stability at elevated temperatures while hindering Li‐ion transport at low temperatures. Here a liquid‐confinement topology is reported that immobilizes a continuous liquid phase within an ultralow‐content (3 wt.%) copolymer scaffold to overcome these limitations. By employing kinetically regulated in situ copolymerization of trifluoroethyl methacrylate and N,N‐dimethyl acrylamide, a sparse yet cross‐linked network is constructed, topologically confining the electrolyte to create uninterrupted Li‐ion conduction pathways. This approach enables the gel electrolyte to resist phase separation or solvent loss up to 90 °C, while maintaining fast ionic conductivity even at −20 °C. The performance of this GPE is validated in Li||LiNi 0.6 Co 0.2 Mn 0.2 O 2 cells (≥ 2.5 mAh cm −2 ), which retain 81.9% capacity over 300 cycles at 90 °C and achieve 97.5% retention at −20 °C. Furthermore, Ah‐scale pouch cells exhibit suppressed gas evolution and resistance to thermal runaway, even under 90 °C cycling conditions. This topology‐guided design bridges the gap between liquid‐like ionic transport and solid‐state safety, providing a scalable solution for high‐energy lithium metal batteries operable across a wide temperature range.
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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".