Production of Carbon Fibers Using a Molten Cu–In Catalyst for Methane Pyrolysis
Bibliographic record
Abstract
Molten metal catalysts for methane pyrolysis and dry reforming are becoming recognized for their potential in decarbonization efforts. Their use in bubble column reactors facilitates continuous operation by allowing the produced carbon to float to the surface for removal. While most reported molten metals produce low-value amorphous carbon or graphitic sheets containing some metals, our study introduces a Cu-In alloy that selectively produces high-purity carbon nanofibers. These nanofibers are tubular and have a smooth or bamboo-like segmented structure with a diameter of approximately 100 nm. We have identified a droplet-based pathway for the growth of these fibers and removal of the droplets, observed consistently across a bubble column reactor, a surface reactor, and both in the absence and presence of carbon dioxide for pyrolysis and dry reforming. The molten Cu-In system is shown to outperform other molten metal catalysts, producing fibers with a purity greater than 99.9% after heat treatment.
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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".