Raman Spectroscopy and Field Emission Scanning Electron Microscopic Studies on Carbon Nanomaterials
Bibliographic record
Abstract
Raman analysis is one of the main methods use to investigate type of graphitized carbon nanomaterials. It provides information on the vibration of crystal lattice, electron structure and regularity of crystal structure of the graphitized carbon materials. In this work the single step chemical vapour deposition (CVD) method was introduced for the direct growth of all as-synthesized carbon nanomaterials; carbon nanotubes (CNTs), carbon nanofiber (CNF), carbon nanosphere chain (CNSC) and CNT heterojunctions (HJCNTs). Series of metal catalysts were formulated from Ni, Fe, Cr and Cu, and were used in the synthesis of the respected carbon nanomaterials (CNMs). By introducing the right combination of the reaction conditions consisting of the formulated catalyst, reaction temperature and flow rate as well as type of carbon source resulted in the formation of different types of carbon nanomaterials. Raman spectra analysis revealed that the used of acetylene and ethanol as the carbon precursors are proficient to produce different form of carbon nanomaterials as depicted by the evolution of the G-band and D-band intensities. The FESEM micrographs obtained confirmed the morphology and types of the respected carbon nanomaterials synthesized in this study.
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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) | 0.002 | 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".