Carbon Nanotube Supported Fluorine Substituted Iron Phthalocyanine Enabling Boosted Polysulfide Redox Conversion Kinetics and Cyclic Stability
Bibliographic record
Abstract
Abstract The sluggish transition and shuttle of polysulfides (LiPS) significantly hinder the application and commercialization of Li−S batteries. Herein, carbon nanotubes (CNTs) supported 10 nm sized iron Hexadecafluorophthalocyanine (FePcF16/CNTs) are prepared using a solid synthesis approach. The well‐exposed FePcF16 molecular improve the LiPS capture efficiency and redox kinetics by its central Fe−N4 units and F functional groups. The strong electron withdraw F groups significantly promote the conjugate effect and decrease the steric hindrance during mass migration procedure. Distribution of relaxation time (DRT) analysis shows that the Fe−N4 units exhibit strong affinity towards LiPS and the F groups further improve the Li+ diffusion rate in Li2S nucleation and oxidation procedure, accomplishing a porous surface on cathode. As a result, the FePcF16/CNTs separator exhibits a high initial capacity of 1136.2 mAh g−1 at 0.2 C, outstanding rate capacity of 624.9 mAh g−1 at 5 C and superior long‐term stability at 2 C surviving 300 cycles with a low capacity decay of 0.43 ‰ per cycle.
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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".