Plasma Functionalization of Carbon Nanotubes for the Synthesis of Stable Aqueous Nanofluids and Poly(vinyl alcohol) Nanocomposites
Bibliographic record
Abstract
Abstract Carbon nanotubes (CNTs) synthesized by direct thermal chemical vapor deposition growth from stainless steel mesh are surface functionalized via an Ar/O2/C2H6 capacitively coupled RF plasma discharge. The open and rigid network of CNTs allows for a high degree of the CNT surface to be treated. As a result, the aqueous nanofluids that are produced by removing the CNTs from the substrate are found to remain stable for extended periods of time (greater than six months). X‐ray photoelectron spectroscopy analysis revealed that oxygen comprised approximately 21 at.% of the functionalized CNT surface. Poly(vinyl alcohol)/CNT nanocomposites produced using the plasma functionalized CNTs are homogenous with excellent dispersion of the CNTs. Mechanically, the 0.75 wt.‐% functionalized‐CNT nanocomposite show 54 and 60% increases in tensile strength and modulus, respectively, over the neat polymer. Little to no change is seen in the degree of crystallinity or the glass transition and melting point temperatures of the nanocomposites. Finally, water content is found to have a significant effect on the polymer and composite's tensile properties. magnified image
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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".