Thermal stability of carbon nanotube-based nanofluids for solar thermal collectors
Bibliographic record
Abstract
Carbon nanotube dispersions are promising candidates for use as working fluids in high-performance solar collectors. However, one major stumbling block in the way of their widespread application is the difficulty in achieving stable nanofluid suspensions at elevated temperatures. In this study, the stability of plasma- and acid-functionalised multi-walled carbon nanotube dispersions at temperatures up to 150°C was investigated. Therminol 55 and propylene glycol were used as the main solvents, while water was used as a reference solvent. The results of UV-VIS-NIR absorption spectroscopy showed that no agglomeration occurred in the plasma-functionalised multi-walled carbon nanotube nanofluids heated to 150°C. However, minor variations were observed in the absorbance of acid-functionalised multi-walled carbon nanotubes in propylene glycol and therminol 55 base fluids at high temperatures.
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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 | 0.001 |
| 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".