Thermoelectric properties of Sn- and Pb-doped Tl9BiTe6 and Tl9SbTe6
Bibliographic record
Abstract
A variety of substitutions in Tl9BiTe6 and Tl9SbTe6 with Sn and Pb, amounting to 14 different samples, were performed by melting the stoichiometric amounts of elements at 923 K, followed by slow cooling. The pulverized powders were sintered using the hot-pressing technique. All samples were of single phase according to the powder X-ray diffraction patterns. Thermoelectric property measurements were performed to investigate the effects of Sn- and Pb-doping on the electrical conductivity, Seebeck coefficient, and thermal conductivity. Increasing the concentration of the dopants caused increases in electrical and thermal conductivity, while decreasing the Seebeck coefficient. Tl9Bi0.90Pb0.10Te6 and Tl9Bi0.85Pb0.15Te6 exhibited the highest power factor. The changes in lattice thermal conductivity were minor and did not follow a clear trend. Competitive ZT values were obtained for Tl9Bi0.95Sn0.05Te6, Tl9Bi0.95Pb0.05Te6, Tl9Sb0.97Sn0.03Te6, and Tl9Sb0.95Pb0.05Te6, namely 0.95, 0.94, 0.83, and 0.71 around 500 K, respectively. Higher dopant concentrations led to lower ZT values.
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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 | 0.001 |
| 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) | 0.002 | 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".