Experimental Study of the Freezing Point of γ-Al <sub>2</sub> O <sub>3</sub> /Water Nanofluid
Bibliographic record
Abstract
Nanofluids are colloidal suspensions made of nanometer-sized particles dispersed in a conventional fluid. Their unusual thermal properties explain intensive investigations for several thermal and industrial applications. In this work, an experimental investigation was performed to measure the freezing point and to study the supercooling point made of alumina γ-Al 2 O 3 nanoparticles with 30 nm diameter size and deionized water. Particles' volume fraction used in this work is ranging from 1% to 4%. The T-historic method based on the measurement of the point of inflexion was performed to measure the thermal properties such as the freezing point and the latent heat of solidification of the nanofluids for different concentrations. The results show that the supercooling degree decreases for the high particles volume concentrations and that the agglomeration does not influence the temperature of the freezing point. However, it makes the freezing process longer.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".