Microscopic revelation of the solid–gas coupling and Knudsen effect on the thermal conductivity of silica aerogel with inter-connected pores
Bibliographic record
Abstract
As a star insulation material, aerogel plays a significant role in saving energy and meeting temperature requirements in industry due to its extremely low thermal conductivity. The prediction of aerogel's thermal conductivity is of great interest in both research and industry, particularly because of the difficulty in measuring the separated gas conductivities directly by experiment. Hence, the proportions of separated gas conduction and solid-gas coupling conduction are debatable. In this work, molecular dynamics simulations were performed on porous silica aerogel systems to determine their thermal conductivities directly. The pore size achieved in the present study was improved significantly, making it possible to include the gas phase in the investigation of aerogel thermal conductivity. The separated solid conductivity [Formula: see text] and the separated gas thermal conductivity [Formula: see text] as well as the effective solid conductivity [Formula: see text] and the effective gas conductivity [Formula: see text] were calculated. The results suggest that the solid-gas coupling effect is negligible in rarefied gas because the enhancement of thermal conduction due to the short cut bridging effect by gas between gaps in the solid is limited. The gas pressure is the most significant factor that affects the solid-gas coupling effect. The large differential between the prediction and the actual value of the thermal conductivity is mainly from the underestimate of [Formula: see text], and not because of ignoring the coupling effect. As a conclusion, the solid-gas coupling effect can be neglected in the prediction of silica aerogel's thermal conductivity at low and moderate gas pressure, i.e., decreasing the gas pressure is the most efficient way to suppress the coupling effect. The findings could be used in multi-scale simulations and be beneficial for improving the accuracy of predictions of aerogel thermal conductivity.
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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) | 0.000 | 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 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".