A Simple Approach to Control the Physical and Chemical Features of Custom-Synthesized N-Doped Carbon Nanotubes and the Extent of Their Network Formation in Polymers: The Importance of Catalyst to Substrate Ratio
Bibliographic record
Abstract
This study intends to reveal the significance of the catalyst to substrate ratio (C/S) on the structural and electrical features of the carbon nanotubes and their polymeric nanocomposites. Here, nitrogen-doped carbon nanotube (N-MWNT) was synthesized via a chemical vapor deposition (CVD) method using three ratios (by weight) of iron (Fe) catalyst to aluminum oxide (Al2O3) substrate, i.e.,1/9, 1/4, and 2/3, by changing the Fe concentration, i.e., 10, 20, and 40 wt.% Fe. Therefore, the synthesized N-MWNT are labelled as (N-MWNTs)10, (N-MWNTs)20, and (N-MWNTs)40. TEM, XPS, Raman spectroscopy, and TGA characterizations revealed that C/S ratio has a significant impact on the physical and chemical properties of the nanotubes. For instance, by increasing the Fe catalyst from 10 to 40 wt.%, carbon purity increased from 60 to 90 wt.% and the length of the nanotubes increased from 1.2 to 2.6 µm. Interestingly, regarding nanotube morphology, at the highest C/S ratio, the N-MWNTs displayed an open-channel structure, while at the lowest catalyst concentration the nanotubes featured a bamboo-like structure. Afterwards, the network characteristics of the N-MWNTs in a polyvinylidene fluoride (PVDF) matrix were studied using imaging techniques, AC electrical conductivity, and linear and nonlinear rheological measurements. The nanocomposites were prepared via a melt-mixing method at various loadings of the synthesized N-MWNTs. The rheological results confirmed that (N-MWNTs)10, at 0.5–2.0 wt.%, did not form any substantial network through the PVDF matrix, thereby exhibiting an electrically insulative behavior, even at a higher concentration of 3.0 wt.%. Although the optical microscopy, TEM, and rheological results confirmed that both (N-MWNTs)20 and (N-MWNTs)40 established a continuous 3D network within the PVDF matrix, (N-MWNTs)40/PVDF nanocomposites exhibited approximately one order of magnitude higher electrical conductivity. The higher electrical conductivity of (N-MWNTs)40/PVDF nanocomposites is attributed to the intrinsic chemical features of (N-MWNTs)40, such as nitrogen content and nitrogen bonding types.
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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".