Novel Flower-like Nickel Sulfide as an Efficient Electrocatalyst for Non-aqueous Lithium-Air Batteries
Bibliographic record
Abstract
In this paper, metal sulfide materials have been explored for the first time as a new choice of bifunctional cathode electrocatalyst materials for non-aqueous lithium-air batteries (LABs). Nickel sulfides with two different morphologies of flower-like (f-NiS) and rod-like (r-NiS) are successfully synthesized using a hydrothermal method with and without the assistance of cetyltrimethyl ammonium bromide. As LAB cathode catalysts, both f-NiS and r-NiS demonstrate excellent catalytic activities towards the formation and decomposition of Li2O2, resulting in improved specific capacity, reduced overpotentials and enhanced cycling performance when compared to those of pure Super P based electrode. Moreover, the morphology of NiS materials can greatly affect LAB performance. Particularly, the f-NiS is more favorable than r-NiS in terms of their application in LABs. When compared to both r-NiS and pure super P materials as LAB cathode materials, this f-NiS catalyst material can give the highest capacity of 6733 mA h g(-1) and the lowest charge voltage of 4.24 V at the current density of 75 mA g(-1) and also exhibit an quite stable cycling performance.
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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".