Native Defects of the Ultranarrow-Bandgap Semiconductor γ-SnSe and Their Effect on Its Electronic, Optical, and Thermoelectric Properties
Bibliographic record
Abstract
SnSe is attractive due to its excellent thermoelectric properties and the scarcity of tellurium. Very recently, γ-SnSe, with an ultranarrow bandgap, was discovered at the nanoscale. It exhibits promising optical properties, including a wide absorption range from IR to UV, suggesting its potential to capture a significant portion of the solar spectrum as an active absorber layer. Here, we explore its electronic properties for optoelectronic and thermoelectric applications. Specifically, we investigate the native defects in γ-SnSe and their effects on its electronic, optical, and thermoelectric properties. Similar to its α-SnSe counterpart, the cation and anion vacancies were found to be the energetically most stable intrinsic defects in γ-SnSe under Se-rich and Sn-rich conditions, respectively. We found that overall defects have a minimal effect on the bandgap and the optical properties, but influence their anisotropy. Additionally, we investigated the thermoelectric properties of γ-SnSe and found the power factor to be comparable to that of its α- Pnma counterpart.
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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) | 0.000 | 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) | 0.000 | 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".