Scalable and Ultrathin Dual Entangled Network Polymer Electrolytes for Safe Solid‐State Sodium Batteries
Bibliographic record
Abstract
Abstract Identifying ultrathin and flexible solid‐state electrolytes with high ionic conductivity and low interfacial resistance is crucial for scale‐up production of solid‐state sodium (Na) metal batteries (SSMBs). However, the challenges of poor processing scalability, insufficient intrinsic mechanical strength, and limited ionic transport capacity remain unaddressed. Herein, an ultrathin 9.7 µm solid‐state electrolyte membrane featuring a dual‐polymer entangled network is meticulously engineered through an arrayed multi‐nozzle electrospinning technique with a swelling and hot pressing process using polyacrylonitrile and poly(ether‐block‐amide), which exhibits an exceptional voltage tolerance, enhanced tensile strength, and superior thermal stability. The soft ether oxygens segments in multiblock copolymers complex with Na + to promote the rapid hopping transport of Na + . Meanwhile, interconnected electronegative channels based on carbonyl and cyanogen groups serve as Na + conduits to smooth ion fluctuations and accelerate Na + selective conduction simultaneously. The obtained inorganic‐organic composite solid electrolyte interface with the improved mechanical strength of ultrathin solid‐state electrolytes effectively suppresses Na dendrites with low overpotential over 500 h. The solid‐state cells paired with layered oxides deliver a capacity retention of over 91.1% between 25 °C and 65 °C, and assembled pouch cells exhibit impressive energy density over 100 cycles, showing great potential for large‐scale application of ultrathin structure in the SSMBs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".