NiS <sub>2</sub> nanosheet arrays on stainless steel foil as binder‐free anode for high‐power sodium‐ion batteries
Bibliographic record
Abstract
Abstract Owing to the wide range and low cost of sodium resources, sodium‐ion batteries (SIBs) have received extensive attention and research. Metal sulfides with high theoretical capacity are used as promising anode materials for SIBs. This paper presents the electrochemical performance of the binder‐free NiS 2 nanosheet arrays grown on stainless steel (SS) substrate (NiS 2 /SS) using an in situ growth and sulfidation strategy as anode for sodium ion batteries. Owing to the close connection between the NiS 2 nanosheet arrays and the SS current collector, the NiS 2 /SS anode demonstrates high rate capability with a reversible capacity of 492.5 mAh·g −1 at 5.0C rate. Such rate capability is superior to that of NiS 2 nanoparticles (NiS 2 /CMC: 41.7 mAh·g −1 at 5.0C, NiS 2 /PVDF: 7.3 mAh·g −1 at 5.0C) and other Ni sulfides (100–450 mAh·g −1 at 5.0C) reported. Furthermore, the initial reversible specific capacity and Coulombic efficiency of NiS 2 /SS are 786.5 mAh·g −1 and 81%, respectively, demonstrating a better sodium storage ability than those of most NiS 2 anodes reported for SIBs. In addition, the amorphization and conversion mechanism during the sodiation/desodiation process of NiS 2 are proposed after investigation by in situ X‐ray diffraction (XRD) measurements of intermediate products at successive charge/discharge stages.
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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 | 0.001 |
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".