(Digital Presentation) H-BN Enhanced Gel Polymer Electrolyte for Solid State Li-Ion Batteries
Bibliographic record
Abstract
In order to address safety concerns of conventional carbonate liquid electrolytes, porous gel polymer electrolytes (GPE) can effectively encapsulate the solution while providing good electrolyte-electrode contact. In this work, a GPE is incorporated with exfoliated 2D hexagonal boron nitride nanosheets (BNNS) as an effective and safe polymer electrolyte for Li-ion batteries. With a facile Dr. Blade approach combined with phase inversion, a high porosity and electrolyte uptake can be maintained while still acting as a stable film. Utilising a 15 wt.% binary polymer mixture of polyvinylidene fluoride (PVDF) and polyethylene oxide (PEO) doped with exfoliated BN flakes, the final GPE is not only more thermal stable but able to effectively suppress dendrite growth through multiple cycles with a high ionic conductivity of 3.03 x10-3 S/cm at ambient conditions. Cell performance with this GPE includes strong cycling performance while sustaining a high coulombic efficiency. Figure 1
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.138 | 0.031 |
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".