THE SYNTHESIS OF A SECOND GENERATION OF NANOFLUIDS BASED ON CARBON NANOTUBES
Bibliographic record
Abstract
In traditional modified methods,the functionalized nanoparticles appear and behave like solids in the absence of solvents.In this paper,a new family of modified nanoparticles,which exhibit liquid-like behavior in the absence of solvents at room temperature,is prepared.The amine-functionalized multi-wall carbon nanotubes (MWNTs) derivative is obtained in a two-step process comprising of oxidation of the tubes with strong acid and then neutralization reaction and hydrogen bonding followed by a surface reaction with dipoly(ethylene glycol) octadecyl amine.The sample is investigated by Fourier transform-infrared spectrometer analysis (FTIR),X-ray diffraction (XRD),thermogravimetric analysis (TGA),differential scanning calorimeter (DSC) and rheological analysis.As a result,the carboxyl and hydroxyl groups were found on the surface of MWNTs,when MWNTs were modified by strong acid. Dipoly(ethylene glycol) octadecyl amine is 40 wt% corresponding to the dense surface coverage of one modifying molecule per 50 carbon atoms of MWNTs.The material is a viscous liquid at room temperature with lower versatility and it can be dispersed in various solvents due to amphiphilic properties of the modifier molecule.Their dispersion,high thermal stability,low vapor pressure and ability to flow at low temperatures make them attractive as lubricants,plasticizers,or film-forming precursors.
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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 | 0.001 | 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".