Facet-Engineered Tungsten Disulfide for Promoting Polysulfide Electrocatalysis in Lithium–Sulfur Batteries
Bibliographic record
Abstract
Distinct facets of an electrocatalyst can promote polysulfide (Li2Sn (n = 4, 6, 8) and Li2Sm (m = 1, 2)) redox kinetics in lithium–sulfur (Li–S) battery chemistry. Herein, we report that the (100) facet of tungsten disulfide (e-WS2) generated in situ by electrochemical pulverization exhibits onset potentials of 2.52 and 2.32 V vs Li/Li+, respectively, for the reduction of polysulfides Li2Sn and Li2Sm, which is unprecedented till date. In a comparable study, bulk WS2 was synthesized ex situ. The transmission electron microscopy (TEM) analysis reveals that the (100) facet was dominant in e-WS2, while the (002) facet was pronounced in bulk WS2. The density functional theory (DFT) analysis indicates that the (100) facet displays metallic-like behavior, which is highly desired for enhanced polysulfide redox kinetics. We believe that the e-WS2 produced can potentially be an excellent electrocatalyst for other applications such as hydrogen evolution reaction (HER), photocatalysis, and CO2 reduction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".