Revealing the Rapid Electrocatalytic Behavior of Ultrafine Amorphous Defective Nb<sub>2</sub>O<sub>5–<i>x</i></sub> Nanocluster toward Superior Li–S Performance
Bibliographic record
Abstract
Abstract The notorious shuttling behaviors and sluggish conversion kinetics of the intermediate lithium polysulfides (LPS) are hindering the practical application of lithium sulfur (Li–S) batteries. Herein, an ultrafine, amorphous, and oxygen-deficient niobium pentoxide nanocluster embedded in microporous carbon nanospheres (A-Nb2O5–x@MCS) was developed as a multifunctional sulfur immobilizer and promoter toward superior shuttle inhibition and conversion catalyzation of LPS. The A-Nb2O5–x nanocluster implanted framework uniformizes sulfur distribution, exposes vast active interfaces, and offers a reduced ion/electron transportation pathway for expedited redox reaction. Moreover, the low crystallinity feature of A-Nb2O5–x manipulates the LPS chemical affinity, while the defect chemistry enhances the intrinsic conductivity and catalytic activity for rapid electrochemical conversions. Attributed to these superiorities, A-Nb2O5–x@MCS delivers good Li–S battery performances, that is, high areal capacity of 6.62 mAh cm–2 under high sulfur loading and low electrolyte/sulfur ratio, superb rate capability, and cyclability over 1200 cycles with an ultralow capacity fading rate of 0.024% per cycle. This work provides a synergistic regulation on crystallinity and oxygen deficiency toward rapid and durable sulfur electrochemistry, holding a great promise in developing practically viable Li–S batteries and enlightening material engineering in related energy storage and conversion areas.
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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".