Fabrication of Ni@SiC composite nanofibers by electrospinning and autocatalytic electroless plating techniques
Bibliographic record
Abstract
In this work, nickel-coated silicon carbide (Ni@SiC) nanofibers were successfully fabricated via electrospinning and autocatalytic electroless plating techniques. The in situ formed nickel oxide (NiO) seeds on the surface of SiC nanofibers were applied to catalyze the plating reaction instead of expensive palladium. The quality of nickel layer was determined by the reaction temperature, deposition time and NiO content in the fibers. After electroless plating for 2 h at 70 °C, the thickness of nickel layer was 60 nm and the average diameter of composite nanofibers was 610 nm. The volume density of the obtained Ni@SiC fibrous membrane was measured to be 1.3 g cm−3. Such composite fibrous membranes with uniform nickel coating and interconnected pore structure possess potential applications as catalysts, supercapacitor and shielding materials.
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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 | 0.001 | 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".