A polymeric composite protective layer for stable Li metal anodes
Bibliographic record
Abstract
Abstract Lithium (Li) metal is a promising anode for high-performance secondary lithium batteries with high energy density due to its highest theoretical specific capacity and lowest electrochemical potential among anode materials. However, the dendritic growth and detrimental reactions with electrolyte during Li plating raise safety concerns and lead to premature failure. Herein, we report that a homogeneous nanocomposite protective layer, prepared by uniformly dispersing AlPO4 nanoparticles into the vinylidene fluoride-co-hexafluoropropylene matrix, can effectively prevent dendrite growth and lead to superior cycling performance due to synergistic influence of homogeneous Li plating and electronic insulation of polymeric layer. The results reveal that the protected Li anode is able to sustain repeated Li plating/stripping for > 750 cycles under a high current density of 3 mA cm−2 and a renders a practical specific capacity of 2 mAh cm−2. Moreover, full-cell Li-ion battery is constructed by using LiFePO4 and protected Li as a cathode and anode, respectively, rendering a stable capacity after 400 charge/discharge cycles. The current work presents a promising approach to stabilize Li metal anodes for next-generation Li secondary batteries.
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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".