Experimental investigation of specific heat of aqueous graphene oxide Al2O3 hybrid nanofluid
Bibliographic record
Abstract
The specific heat of aqueous graphene+Al2O3 (1:1) hybrid nanofluid was measured using the cooling method. The influence of nanoparticle mass fraction and temperature on the specific heat capacity of the hybrid nanofluids was investigated, the specific heat of the hybrid nanofluid was compared with that of aqueous graphene oxide nanofluid and Al2O3 nanofluid. A fitted formula of the specific heat of the hybrid nanofluid was proposed based on the experimental data. It indicates that the specific heat reduction ratio increases with increase of nanoparticle fraction and the maximum reduction ratio is 7% at 0.15 wt.% at 20?C. The mass fraction of nanoparticle affects the specific heat of hybrid nanofluid more significantly at lower temperature. Temperature impacts the specific heat more distinctly than the nanoparticle fraction. The specific heat increases with temperature and the maximum specific heat reduction ratio of the hybrid nanofluid diminishes from 7% at 20?C to 2% at 70?C at the mass fraction of 0.05%.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".