Catalytic pyrolysis of high-density polyethylene for the production of carbon nanomaterials: effect of pyrolysis temperature
Bibliographic record
Abstract
A two-stage reaction process is followed to convert high-density polyethylene (HDPE) into carbon nanofilaments (CNFs) and hydrogen-rich gas. The experiments are performed in a continuous mode in a two-stage quartz reactor: thermal pyrolysis of HDPE followed by the catalytic decomposition of the pyrolysis gases over a nickel catalyst prepared from mining residues. To examine the effect of the pyrolysis temperature on the yield and quality of the final products, two steps were followed. First, non-catalytic pyrolysis experiments were run at different temperatures (600, 650, and 700 °C), and the products were examined. Second, pyrolysis–catalysis experiments were performed at the same pyrolysis temperatures and a fixed catalytic temperature (600 °C) to examine the CNF and hydrogen yields. The results showed that the production of carbon nanomaterials (CNMs) and H2 is optimal at 650 °C, with yields of 70.8 and 38.0 wt%, respectively. Scanning electron microscopy (SEM) revealed the presence of carbon filaments with different diameters and lengths at the three different temperatures. Moreover, thermogravimetric analysis (TGA) confirmed that the produced carbon is filamentous, with the presence of amorphous carbon at 700 °C.
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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) | 0.001 | 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 | 0.001 |
| 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".