Enhanced Thermoelectric Performance of SnSe Thin Film via Simultaneous Optimization of Texture and Carrier Concentrations
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Bibliographic record
Abstract
ABSTRACT Polycrystalline SnSe thin film materials have gained increasing attention as a promising solution for fabricating microscale, flexible, self‐powered electronic components in the field of thermoelectric (TE) materials and devices. However, it is still a great challenge to simultaneously achieve preferred crystal orientation and optimize carrier concentration for SnSe thin films, which are two crucial factors affecting the TE performance, due to the high volatility of Se. Herein, a simple and scalable method using the magnetron co‐sputtering technique with SnSe 2 and SnSe targets is proposed for preparing highly textured polycrystalline SnSe thin films with appropriate carrier concentration. It was found that during the high‐temperature deposition process, SnSe 2 transforms into SnSe, improving their anisotropy of electronic bands around the valley extrema, inducing localized strain field and stacking faults, and the incorporation of Se facilitates an increase in carrier concentration. The co‐sputtered SnSe thin films show a 45% higher power factor of 2.77 μW cm −1 K −2 compared to that constructed by mono‐sputtered SnSe films with the SnSe target alone. Additionally, localized strain field and stacking faults also serve as centers for phonon scattering, thereby reducing lattice thermal conductivity. Consequently, the estimated zT value of 0.65 at 650 K of the polycrystalline SnSe film reaches a relatively high level.
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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 | 0.000 | 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)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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