Design Unsaturated Selenium Coordinated NbSe<sub>2‐x</sub> as Multifunctional Sulfur Electrocatalyst toward Fast and Durable Sulfur Reduction Reaction
Bibliographic record
Abstract
Abstract Lithium‐sulfur (Li‐S) battery are considered as the next generation energy storage system owing to their ultra‐high theoretical specific capacity and energy density. However, the commercialization of Li‐S battery is still hindered by the intrinsically low conductivity of sulfur, sluggish catalytic conversion and notorious shuttle effect of polysulfides. The implantation of defects in sulfur electrocatalyst can effectively increase its conductivity and catalytic efficiency of lithium polysulfides, but the current mainstream defective materials are limited and lack of in‐depth research. Herein, a defective niobium selenide (NbSe2‐x) nanosheet sulfur electrocatalyst is constructed with enriched selenium defects, which demonstrates strong interaction with sulfur species, endowing NbSe2‐x with rapid and reliable sulfur reduction reaction. As a result, the Li‐S cell with NbSe2‐x exhibits excellent multiplicative performance in both coin cell and pouch cell, which maintains stable cycling for over 2000 cycles under 5 C, corresponding to a low‐capacity fading rate of 0.024% per cycle. Ah level pouch cell is also fabricated, showing a decent energy density of 378 Wh kg−1. This creative strategy not only emphasizes the importance of selenium defect engineering in Li‐S batterie toward practical application, but also enlightens the material engineering to realize superior performance in related energy storage and conversion area.
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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".