Enhancing thermoelectric properties of ScN films through twin domains
Bibliographic record
Abstract
Tailoring thermoelectric properties of ScN-based materials is of vital importance for their application, particularly at high operating temperatures. Here, we report on the thermoelectric properties of the ScN layers deposited on MgO (001) substrates by the DC reactive magnetron sputtering. The microstructure of the produced thin films is examined by X-ray diffraction and atomic force microscopy, while their chemical composition and contamination by defects are determined by X-ray photoelectron spectroscopy. The effect of temperature on the phonon properties of ScN layers, having implications for their thermoelectric properties, is explored by Raman spectroscopy. The results of our experiments are confronted with those following from the first-principles studies. We find that the ScN/MgO(001) layers with twin-domain structure reveal enhanced thermoelectric properties at elevated temperature as compared to those measured for almost defect- and domain-free layers, namely, enlarged Seebeck coefficient by about 30% and over two and a half times increased figure of merit at 800 K. Therefore, structural twin domains in thin ScN film appear to be a simple and rather stable solution for the improvement of its thermoelectric properties at elevated temperatures.
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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) | 0.000 | 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 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".