Biobased Self-Growing Approach toward Tailored, Integrated High-Performance Flexible Lithium-Ion Battery
Bibliographic record
Abstract
Here we present an innovative, universal, scalable, and straightforward strategy for cultivating a resilient, flexible lithium-ion battery (LIB) based on the bacterial-based self-growing approach. The electrodes and separator layers are integrated intrinsically into one unity of sandwich bacterial cellulose integrated film (SBCIF), with various active material combinations and tailored mechanical properties. The flexible LIB thereof showcases prominent deformation tolerance and multistage foldability due to the unique self-generated wavy-like structure. The LTO|LFP (Li 4 Ti 5 O 12 and LiFePO 4 ) SBCIF-based flexible LIB demonstrates reliable long-term electrochemical stability with high flexibility, by exhibiting a high capacity retention (>95%) after 500 cycles at 1C/1C after experiencing a 10 000 bending/flattening treatment. The LTO|LFP SBCIF battery subjected to a simultaneous bending/flattening and cycling experiment shows an extraordinary capacity retention rate (>68%) after 200 cycles at 1C/1C. The biobased self-growing approach offers an exciting and promising pathway toward the tailored, integrated high-performance flexible LIBs.
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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 | 0.000 |
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 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".