In situ removal of amorphous carbon from single-walled carbon nanotubes synthesized by induction thermal plasma
Bibliographic record
Abstract
In this work, a simple, efficient and cost-effective in situ purification method has been developed based on gas-phase oxidation, in an effort to increase purity of single-walled carbon nanotubes (SWNT) in the course of SWNT synthesis by induction thermal plasmas. This newly developed purification method has the following advantages compared with the conventional off-line gas-phase oxidation techniques; 1) residual heat carried by plasma gases from the reactor can be utilized as a heat source for the thermal oxidation reaction; 2) oxidizing reactants can pass through the SWNT soot collected on the surface of metallic filters, resulting in more uniform and effective etch of amorphous carbons; 3) this one-step process is basically continuous and easy to be scaled up. In the purification experiments, for the thermal oxidation of the SWNT soot, pre-heated oxygen is injected into the collection chamber during the SWNT synthesis with three different oxygen flow rates of 5, 7.5 and 10 vol% 02, and then subsequent changes in the SWNT soot are analyzed by various material characterization techniques, such as thermogravimetric analysis (TGA), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and Raman spectroscopy. The results clearly show that the major by-product of amorphous carbons can be successfully eliminated by this method and the purity of the SWNT has been increased approximately from 35 wt% to 60 wt% due to preferential removal of amorphous carbons. The parametric study on the effect of the flow rate also suggests that the most effective flow rate of the oxidizing gas is around 10 vol%. However, the diameter distribution of the SWNT samples has been narrowed during the in situ thermal oxidation process because of a significant loss of thin nanotubes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".