Effect of mixed occupancies on the thermoelectric properties of BaCu<sub>6−x</sub>Se<sub>1−y</sub>Te<sub>6+y</sub> polychalcogenides
Bibliographic record
Abstract
The title materials have been reported earlier to be p-type thermoelectrics when x = 0.1 and y = 0. Here, we studied the properties after varying the Cu and the Se/Te concentrations. At first, materials with the same nominal Cu concentration, 5.9 Cu per formula unit, and different Se/Te ratios were prepared. The different thermoelectric properties indicated that the Se/Te ratio strongly affected the Cu deficiency, which is directly responsible for the charge carrier concentration. Single crystal structure data revealed the Cu amount to be less than 5.8 per formula unit when y = 0.4; therefore a sample of nominal composition "BaCu5.74Se0.46Te6.54" was also studied. This sample exhibited an electrical conductivity of 685 Ω-1 cm-1 at room temperature, which is almost three times larger than in case of "BaCu5.9SeTe6", in accord with the lower Cu amount causing a larger hole concentration. The larger mass fluctuation on the Se/Te site resulted in a lower lattice thermal conductivity, but the decreased Seebeck coefficient mitigated a performance increase in form of a higher figure-of-merit. In contrast to other Cu chalcogenides, the data are reproducible under the measurement conditions.
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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".