Advanced Composite Solid Electrolyte Architecture Constructed with Amino‐Modified Cellulose and Carbon Nitride via Biosynthetic Avenue
Bibliographic record
Abstract
Abstract Polyethylene oxide (PEO) solid electrolytes are regarded as a promising candidate for all‐solid‐state lithium batteries owing to their high safety and interfacial compatibility. However, PEO electrolyte is plagued by relatively weak structural strength and unsatisfactory Li + conductivity. Herein, a mechanically strong and Li + conductively favorable cellulosic scaffold of PEO is fabricated through amino (‐NH 2 ) modification and g‐C 3 N 4 (CN) incorporation of bacterial cellulose (BC) under a microbial circumstance. The biologically ‐NH 2 modified BC (B‐NBC) is entangled with CN nanosheets (CN@B‐NBC) through an in situ secretion of nanocellulose followed by hydrogen bond‐induced self‐assembly. The ‐NH 2 groups from B‐NBC weaken the complexation of Li + with its counterpart, thus facilitating the release of more free Li + . CN with strong C‐N covalence and extra lone electrons of N further strengthens the BC skeleton and meanwhile offers sufficient anchors for Li + migration. After infiltrating by LiTFSI/PEO (LP), the LP/CN@B‐NBC composite solid electrolyte (CSE) exhibits high lithium transference number and ionic conductivity. Upon coupling with LiFePO 4 cathode, the full battery exhibits a remarkably high specific capacity, superior rate capability, and decent cycling stability. This work pioneers the attempts of chemical decoration and ingredient incorporation of BC architecture in CSE with the aid of a bottom‐up biosynthetic avenue.
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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".