Tailoring Vertically Aligned Inorganic‐Polymer Nanocomposites with Abundant Lewis Acid Sites for Ultra‐Stable Solid‐State Lithium Metal Batteries
Bibliographic record
Abstract
Abstract Nanocomposite solid polymer electrolytes are considered as a promising strategy for solid‐state lithium metal batteries (SSLMBs). However, the randomly dispersed fillers in the polymer matrix with limited Li + transference number and insufficient ionic conductivity severely sacrifice the ion transport capacity, thus restricting their practical application. To tackle these issues, a magnetic field‐assisted alignment strategy is proposed to disperse the vertically aligned akaganéite nanotube in the polymer matrix as an inorganic‐polymer nanocomposite solid‐state electrolyte for ultra‐stable SSLMBs. The metal cations as Lewis acid sites can grab anions to promote the dissociation of Li salts while the sufficient oxygen and hydroxyl functional group offer abundant Li‐ion migration sites for favored ion transportation. At the same time, the vertically aligned akaganéite/polymer interface combined with the above synergistic effects can establish oriented channels inside solid‐state electrolyte, which significantly elevates its ionic conductivity. Specially, an organic‐inorganic dual‐layer solid‐electrolyte interface is formed to uniform Li deposition and suppress the dendrite growth. The beneficial effect of the vertically aligned network is also demonstrated in full cell and pouch cell where remarkable 2000 cycles with a capacity decay of 0.012% per cycle can be achieved.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".