Quantitative stability analyses of multiwall carbon nanotube nanofluids following water/ice phase change cycling
Bibliographic record
Abstract
Multiwall carbon nanotube nanofluids are regularly investigated for phase change enhancement between liquid and solid states owing to their improved heat transfer properties. The potential applications are numerous, the most notable being latent heat thermal energy storage, but the success of all nanofluid-assisted technologies hinges greatly on the ability of nanoparticles to remain stably dispersed after repeated phase change cycles. In this report, the stability of aqueous nanofluids made from oxygen-functionalized multiwall carbon nanotubes (f-MWCNTs) was profiled over the course of 20 freeze/thaw cycles. Sonication was used after each cycle to re-disperse clusters formed from the crystallization process. This study offers a quantitative evaluation of f-MWCNT-nanofluid stability as a result of phase change through optical characterization of concentration and particle size. It also provides insight into the integrity of the surface functionalities through zeta potential and XPS analyses. Concentration and particle size measurements showed moderate and consistent recoverability of f-MWCNT dispersion following ultrasonication. XPS measurements of solid-state MWCNTs exposed to freeze/thaw cycling in water, and zeta potential analyses of the nanofluids indicate that the surface oxygen content is preserved throughout phase change and over repeated cycles. These results suggest a resilience of oxygen-functionalized MWCNTs to the freezing and thawing of water, which is ideal for their utilization as phase change enhancers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 teacher head, 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".