One‐Step In‐Situ Growth of Core–Shell SiC@Graphene Nanoparticles/Graphene Hybrids by Chemical Vapor Deposition
Bibliographic record
Abstract
A one‐step in‐situ route to free standing core–shell silicon carbide in graphene nanoparticles on monolayer graphene is presented. The core–shell SiC@Graphene nanoparticle growth is realized by a simple chemical vapor deposition (CVD) process where carbon and silica precursors are simultaneously introduced into the growth chamber. This process permits the synthesis of a monolayer graphene sheet dressed with silicon carbide nanoparticles in a single CVD step, with the product controlled by growth temperature and the carbon/SiO2 exposure time. Growth of a high density SiC@Graphene distribution on a continuous graphene layer requires long exposure times (>1 h) and high temperature (1000 °C). The growth process proceeds by a carbothermal mechanism. The simultaneous growth of graphene and SiC nanoparticles enables uniform core–shell SiC@Graphene nanoparticle formation rather than SiC/carbon nanofiber growth. As a proof of concept, the functionalization of preformed nanoparticle graphene surface with a diazonium salt is studied, demonstrating an increase in grafting rate with increasing nanoparticle population. This work provides a general procedure for one‐step synthesis, with further investigation required to develop precursors for hybrid core–shell CVD material growth.
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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".