Development of a high-accuracy thermal interface material tester
Bibliographic record
Abstract
An experimental apparatus has been designed and constructed to accurately measure the next generation of high-performance thermal interface materials with unprecedented precision and accuracy. The apparatus is based on a common implementation of ASTM D5470 using meter bars. However, the apparatus in the present study is unique in that it utilizes small thermistors to make precise thermal measurements (plusmn0.003 K). These measurements are used to calculate the thermal impedance at the interface of two conducting bodies while keeping input power at a minimum. Furthermore, a robust and conservative uncertainty analysis is employed to calculate how the measured uncertainties contribute to the calculated quantities of thermal impedance and effective thermal conductivity. Baseline tests are performed to demonstrate the sensitivity and uncertainty of the apparatus by measuring the contact resistance of the meter bars in contact with each other as a representative low-thermal- impedance case. A contact thermal impedance as low as 2.81E-5 m2ldrK/W was measured with a calculated absolute uncertainty of approximately 2%. The effective thermal conductivity of a gap pad was also measured to further validate the apparatus.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".