Advancing the reliability of thermoelectric materials: A case study of silicides through statistics
Bibliographic record
Abstract
This work presents a statistical study of mechanical properties of a pair of silicide thermoelectric (TE) materials, p-type higher manganese silicide (HMS), and bismuth-doped n-type magnesium silicide stannide. The fracture strength of each material was examined with a statistically significant number of samples to obtain useful information for subsequent engineering work. Furthermore, to lend credibility to our measurements, we applied an ASTM standard (ASTM C1161) toward the determination of the mechanical properties instead of using nonstandard approaches. This approach, rarely undertaken for TE materials, was enabled by following large-scale synthetic capabilities that met the size requirements of this standard without compromising the thermoelectric figure-of-merit. The distributions of fracture strengths of the pair of silicide materials were established, and the fracture mechanisms elucidated through analyses of the fractured surfaces. Using this information, we were able to improve the fracture strength of p-type HMS through a minor addition of vanadium without compromising the figure-of-merit ZT. Together, these results advance the reliability of silicide TE materials, making them attractive candidates for large-scale deployment.
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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 | 0.000 | 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 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".