Low‐Bandgap Se‐Deficient Antimony Selenide as a Multifunctional Polysulfide Barrier toward High‐Performance Lithium–Sulfur Batteries
Bibliographic record
Abstract
Abstract The shuttling behavior and sluggish conversion kinetics of the intermediate lithium polysulfides (LiPSs) represent the main obstructions to the practical application of lithium–sulfur (Li–S) batteries. Herein, an anion‐deficient design of antimony selenide (Sb2Se3−x) is developed to establish a multifunctional LiPS barrier toward the inhibition of polysulfide shuttling and enhancement of battery performance. The defect chemistry in the as‐developed Sb2Se3−x promotes the intrinsic conductivity, strengthens the chemical affinity to LiPSs, and catalyzes the sulfur electrochemical conversion, which are verified by a series of computational and experimental results. Attributed to these unique superiorities, the obtained LiPS barrier efficiently promotes and stabilizes the sulfur electrochemistry, thus enabling excellent Li–S battery performance, e.g., outstanding cyclability over 500 cycles at 1.0 C with a minimum capacity fading rate of 0.027% per cycle, a superb rate capability up to 8.0 C, and a high areal capacity of 7.46 mAh cm−2 under raised sulfur loading. This work offers a defect engineering strategy toward fast and durable sulfur electrochemistry, holding great promise in developing practically viable Li–S batteries as well as enlightening the material design of related energy storage and conversion systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".