Electrospun ceramic nanofibers as 1D solid electrolytes for lithium batteries
Bibliographic record
Abstract
All-solid-state lithium batteries (ASSLBs) are undoubtedly among the most promising technologies to replace conventional lithium-ion batteries. Their key component is a thin solid-state electrolyte, which is safer than its flammable liquid counterpart and enables the use of metallic lithium, thus ensuring high energy densities (over 500 W h kg −1 ). Several solid electrolytes are currently being investigated, such as NASICON-like materials, perovskites, and garnets. Typical techniques used to synthesize most such electrolytes still involve prolonged high-temperature calcination and sintering steps. An alternative approach is to couple electrospinning with the well-known sol–gel method to lower the temperatures and synthesis times and simultaneously exploit the benefits of using anisotropic nanostructured materials. In this review, we discuss advances in the synthesis of ceramic nanofibrous materials having high ionic conductivity and present our perspective regarding their potential application as electrolytes in ASSLBs.
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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 | 0.001 |
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".