A Natural Biopolymer Film as a Robust Protective Layer to Effectively Stabilize Lithium‐Metal Anodes
Bibliographic record
Abstract
Abstract Li metal is considered as an ideal anode for Li‐based batteries. Unfortunately, the growth of Li dendrites during cycling leads to an unstable interface, a low coulombic efficiency, and a limited cycling life. Here, a novel approach is proposed to protect the Li‐metal anode by using a uniform agarose film. This natural biopolymer film exhibits a high ionic conductivity, high elasticity, and chemical stability. These properties enable a fast Li‐ion transfer and feasiblity to accomodate the volume change of Li metal, resulting in a dendrite‐free anode and a stable interface. Morphology characterization shows that Li ions migrate through the agarose film and then deposit underneath it. A full cell with the cathode of LiFPO4 and an anode contaning the agarose film exhibits a capacity retention of 87.1% after 500 cycles, much better than that with Li foil anode (70.9%) and Li‐deposited Cu anode (5%). This study provides a promising strategy to eliminate dendrites and enhance the cycling ability of lithium‐metal batteries through coating a robust artificial film of natural biopolymer on lithium‐metal anode.
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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".