Effect of interfacial thermal resistance and nanolayer on estimates of effective thermal conductivity of nanofluids
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Bibliographic record
Abstract
Colloidal suspensions of nanoparticles (nanofluids) are materials of interest for thermal engineering, because their heat transfer properties are typically enhanced as compared to the base fluid one. Effective medium theory provides popular models for estimating the overall thermal conductivity of nanofluids based on their composition. In this article, the accuracy of models based on the Bruggeman approximation is assessed. The sensitivity of these models to nanoscale interfacial phenomena, such as interfacial thermal resistance (Kapitza resistance) and fluid ordering around nanoparticles (nanolayer), is considered for a case study consisting of alumina nanoparticles suspended in water. While no significant differences are noticed for various thermal conductivity profiles in the nanolayer, a good agreement with experiments is observed with Kapitza resistance ≈10−9 m2K/W and sub-nanometer nanolayer thickness. These results confirm the classical nature of thermal conduction in nanofluids and highlight that future studies should rather focus on a better quantification of Kapitza resistance at nanoparticle-fluid interfaces, in order to allow bottom up estimates of their effective thermal conductivity.
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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 | 0.000 |
| 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 it