Thermal transport across a pair of thin silicon films with the presence of minute vacuum gap: effect of film thickness on thermal characteristics
Bibliographic record
Abstract
Energy transport across a pair of thin silicon films with the vacuum gap at the films interface is studied. The Boltzmann transport equation is incorporated in the analysis and the solution for the transient frequency-dependent phonon distribution across the films pair is presented. To assess the phonon characteristics, equivalent equilibrium temperature is introduced, which resembles the average energy of all phonons around a local point when they redistribute adiabatically to an equilibrium state. Because the gap size is comparable to the mean free path of silicon, a near-field radiation heat transfer is incorporated across the film edges at the interface. The frequency cutoff method is used at the interface of the films and the phonons jump across the gap resembling the ballistic phonon contribution to the energy transport is accommodated. The thermal conductivity data predicted are validated with the data obtained from the previous study. The effect of near-field radiation heat transfer on temperature increase at the edges of the film, across the gap interface, is not considerable as compared to that corresponding to phonons transmitted across the gap. Increasing the first film thickness increases temperature difference across the gap, which is more pronounced for large gap sizes.
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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 | 0.000 | 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) | 0.001 | 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".