Spatially Sequential Growth of Various WSi<sub>2</sub> Networked Nanostructures and Mechanisms
Bibliographic record
Abstract
Various WSi 2 nanostructures including networked nanorods (NNWs), networked nanoribbons (NNRs), and nanosheets (NSs) were sequentially (spatial) synthesized in a controlled manner via a single-step chemical vapor deposition method. Their morphology, structure, and composition were characterized by scanning and transmission electron microscopes and X-ray diffraction. The nanostructures are 6–10 nm in thickness and several micrometers in length. The results reveal that the formation of WSi 2 nanostructures is governed by a vapor solid mechanism and the concentration of reactive species plays a crucial role in controlling the formation of the various morphologies of the synthesized nanostructures. The time-dependent growth study shows that the nanostructures feature two-dimensional growth of WSi 2, resulting in nanonets and nanosheets. Cyclic voltammetry measurements of these nanostructures demonstrate the chemical capacitance characteristics of WSi 2 nanosheets and nanoribbons. Not only has this study paved a new route for preparing various nanostructures, but also these nanostructures are of great interest for nanodevices and electrochemical applications.
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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".