Preparation of Carbon Nanotubes by Seeded Catalyst Method with Palm Oil as Starting Material
Bibliographic record
Abstract
Carbon Nanotubes (CNTs) are produced by using Thermal Chemical Vapor Deposition (TCVD). The function of support catalyst is to optimize used of the catalyst. The properties of CNTs produced are determined by Fourier Transmission Infrared Spectroscopy (FTIR). The catalyst was prepared by sol‐gel method where Cobalt, Iron and Nickel were used. Different percentage of support catalyst was added with the catalyst. The palm oil was used as precursor to synthesize the CNTs. The CNTs was then collected and characterized by using FTIR. Increasing the percentage of support catalyst (zeolite) contributes to the unstableness of carbon bonding of CNTs. The CNTs will vibrate more and absorb more energy. From the FTIR peaks, the absorbance energy of CNTs depends on the types of catalyst used.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".