Synthesis of single-walled carbon nanotubes by induction thermal plasma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The production of high quality single-walled carbon nanotubes (SWCNTs) on a bulk scale has been an issue of considerable interest. Recently, it has been demonstrated that high quality SWCNTs can be continuously synthesized on large scale by using induction thermal plasma technology. In this process, the high energy density of the thermal plasma is employed to generate dense vapor-phase precursors for the synthesis of SWCNTs. With the current reactor system, a carbon soot product which contains approximately 40 wt% of SWCNTs can be continuously synthesized at the high production rate of ∼100 g/h. In this article, our recent research efforts to achieve major advances in this technology are presented. Firstly, the processing parameters involved are examined systematically in order to evaluate their individual influences on the SWCNT synthesis. Based on these results, the appropriate operating conditions of the induction thermal plasma process for an effective synthesis of SWCNTs are discussed. A characterization study has also been performed on the SWCNTs produced under the optimum processing conditions. Finally, a mathematical model of the process currently under development is described. The model will help us to better understand the synthesis of SWCNTs in the induction plasma process.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it