Improved Bulk Materials with Thermoelectric Figure‐of‐Merit Greater than 1: Tl<sub>10–<i>x</i></sub>Sn<sub><i>x</i></sub>Te<sub>6</sub> and Tl<sub>10–<i>x</i></sub>Pb<sub><i>x</i></sub>Te<sub>6</sub>
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Bibliographic record
Abstract
Noting the steadily worsening problem of depleted fossil fuel sources, alternate energy sources have become increasingly important; these include thermoelectrics, which may use waste heat to generate electricity. To be economically viable, the thermoelectric figure‐of‐merit, zT , which is related to the energy conversion efficiency, needs to be in excess of unity ( zT > 1). Tl 4 SnTe 3 and Tl 4 PbTe 3 were reported to attain a thermoelectric figure‐of‐merit zT max = 0.74 and 0.71, respectively, at 673 K. Here, the thermoelectric properties of both materials are presented as a function of x in Tl 10– x Sn x Te 6 and Tl 10– x Pb x Te 6 , with x varying between 1.9 and 2.05, culminating in zT values in excess of 1.2. These materials are charge balanced when x = 2, according to (Tl + ) 8 (Sn 2+ ) 2 (Te 2− ) 6 and (Tl + ) 8 (Pb 2+ ) 2 (Te 2− ) 6 (or: (Tl + ) 4 Pb 2+ (Te 2− ) 3 ). Increasing x causes an increase in valence electrons, and thus a decrease in the dominating p‐type charge carriers. Larger x values occur with a smaller electrical conductivity and a larger Seebeck coefficient. In each case, the lattice thermal conductivity remains under 0.5 W m −1 K −1 , resulting in several samples attaining the desired zT max > 1. The highest values thus far are exhibited by Tl 8.05 Sn 1.95 Te 6 with zT = 1.26 and Tl 8.10 Pb 1.90 Te 6 with zT = 1.46 around 685 K.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it