Thermal Contact Resistance at Rough Ceramic–Metallic Joints
Bibliographic record
Abstract
Engineered ceramics are widely used in a variety of industries in demanding thermal environments. In power electronics, for example, the thermal contact resistance (TCR) between ceramic insulators and metallic heat sinks can be a significant bottleneck to heat transfer. Despite this, the existing TCR literature has (for the most part) focused on metal–metal contacts. In this study, the thermal contact resistance between aluminum oxide, alumina nitride, and stainless steel is experimentally measured using the guarded heat flow meter technique, as per ASTM E1530 (“Standard Test Method for Evaluating the Resistance to Thermal Transmission of Materials by the Guarded Heat Flow Meter Technique,” ASTM International STD E1530-11, West Conshohocken, PA, 2016). Tests are conducted both under vacuum and under atmospheric pressure in order to compare results with existing metal–metal TCR models. Experimental results are within a 25% rms relative difference of existing statistical-based conforming rough plastic TCR models.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".