Functionalization and Toxicity Effect of Multi-walled Carbon Nanotubes with Urea Derivatives<i>via</i>Microwave Irradiation
Bibliographic record
Abstract
Nanotubes were used in medical sciences especially in drug delivery system and cancer therapy. In this study, we have reported a highly efficient approach to functionalization of carboxylated multi-walled carbon nanotubes (MWNT-COOH) by 4,4'-oxydianiline or 4,4'-oxybis(2-nitroaniline) and the latter modification with phenylisocyanate for producing urea derivatives under microwave irradiation. Reducing the reaction time to the order of minutes and the number of steps in the reaction procedure is the major advantage of this procedure respect to conventional functionalization methods. These reactions were carried out in 25 min under microwave conditions, and the results were similar to what was achieved in 4 days using conventional methods. The interesting point is that modified MWNTs can be homogeneously dispersed in DMF without sonication, and the dispersed MWNTs does not sediment in 3 month. All products were characterized by Fourier transform infrared and Raman spectroscopy, scanning electron microscope, elemental analysis, TGA, DTG and cellular investigations. Toxicity assays with Stem cells and MTT test for measurement of viable cell numbers were also performed. Cellular results showed high toxicity of MWNT-Amide samples especially with NO2 groups.
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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) | 0.000 | 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 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".