Divacancy and resonance level enables high thermoelectric performance in n-type SnSe polycrystals
Bibliographic record
Abstract
Abstract N -type polycrystalline SnSe is considered as a highly promising candidates for thermoelectric applications due to facile processing, machinability, and scalability. However, existing efforts do not enable a peak ZT value exceeding 2.0 in n -type polycrystalline SnSe. Here, we realized a significant ZT enhancement by leveraging the synergistic effects of divacancy defect and introducing resonance level into the conduction band. The resonance level and increased density of states resulting from tungsten boost the Seebeck coefficient. The combination of the enhanced electrical conductivity (achieved by increasing carrier concentration through WCl 6 doping and Se vacancies) and large Seebeck coefficient lead to a high power factor. Microstructural analyses reveal that the co-existence of divacancy defects (Se vacancies and Sn vacancies) and endotaxial W- and Cl-rich nanoprecipitates scatter phonons effectively, resulting in ultralow lattice conductivity. Ultimately, a record-high peak ZT of 2.2 at 773 K is achieved in n -type SnSe 0.92 + 0.03WCl 6 .
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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".