An orderly arranged dual-role MIL-53(Al) nanorods array rooted on carbon nanotube film for long-life and stable lithium-sulfur batteries
Bibliographic record
Abstract
It is of great value to synchronously resolve the critical issues of the polysulfide shuttle and dendrite growth in lithium-sulfur (Li-S) batteries. Herein, a bifunctional Al-based Material of Institute Lavoisier-53 (MIL-53(Al))/carbon nanotube (MIL-53/CNT) composite is reported for this matter, which was constructed by growing an ordered MIL-53(Al) nanorods array on the CNT film. For the sulfur cathode, the proposed structure serves as a multifunctional interlayer to block polysulfides and accelerate their catalytic conversion, thus efficaciously inhibiting the shuttle effect. Meanwhile, when applied as the anode host material (Li@MIL-53/CNT), the flexible CNT film serves as a self-standing framework to accommodate Li metal and alleviate the volume expansion, while the uniform ion channels built by the MIL-53(Al) nanorods array along with the abundant oxygen groups can homogenize Li ion diffusion, enabling a steady Li plating/stripping behavior and limiting the dendrite growth. Not surprisingly, Li-S full battery with MIL-53/CNT interlayer and Li@MIL-53/CNT anode delivers an appreciable specific capacity of 735 mAh·g−1 and excellent cycle durability at 5 C, presenting a limited capacity decay of 0.03% per cycle in 500 cycles. Besides, an impressive cycle stability and rate capability are also achieved at high-sulfur loading and lean electrolyte conditions.
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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".