Thermal Stability of Plasma Generated Oxygenated Functionalities on Carbon Nanotubes
Bibliographic record
Abstract
Colloidal suspensions of functionalized carbon nanotubes (CNT nanofluids) have the potential to be used in a variety of applications, many of which require operation at elevated temperatures. In this study, we examine what effect exposure to an argon/oxygen/ethane RF glow discharge plasma has on the surface chemistry and structure of CNTs and what happens to the plasma‐generated functionalities at high temperatures. An analysis performed using X‐ray photoelectron spectroscopy and Raman spectroscopy indicates that longer and higher power plasma treatments decrease the sp2 graphitic nature of the CNTs without increasing the degree of oxygen functional groups. Heating of the functionalized‐CNTs up to 350 °C in air and 600 °C in argon, both lead to a substantial decrease in the surface oxygen concentration, which can be attributed to the decomposition of carboxylic functionalities at low temperatures (< 350 °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) | 0.000 | 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".