The effects of hydrogen proportion on the synthesis of carbon nanomaterials with gaseous detonation (deflagration) method
Bibliographic record
Abstract
Using ferrocene, H 2 and O 2 , Carbon nanomaterials were prepared with gaseous detonation (deflagration) method. The effects of H 2 on the phase and morphology of carbon nanomaterials were studied by various proportions of H 2 in the reaction. The prepared samples were characterized by x-ray diffractometer, transmission electron microscope and Raman spectrometer. The results show that hydrogen proportion has a great influence on the phase and morphology of carbon nanomaterials. The high hydrogen proportion leads to much unreacted hydrogen, which could protect the iron atom from oxidation of carbon and dilute the reactants contributing to uniform particle size. In addition, the graphitization degree of multi-walled carbon nanotubes, observed in samples with high H 2 proportion, is high enough to see the lattice fringes, but the degree of graphitization of whole sample is lower than which fabricated with low H 2 proportion, and it may result from the low energy generation.
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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".