Synthesis and X-ray photoelectron spectroscopy (XPS) and thermoelectric studies of ternary Bi<sub>2</sub>(Te<sub>0.5</sub>Se<sub>0.5</sub>)<sub>3</sub> mixed-metal chalcogenide thin films by the arrested precipitation technique
Bibliographic record
Abstract
Arrested precipitation technique (APT) has been successfully employed for the deposition of Bi2(Te0.5Se0.5)3 thin films. Analytical grade bismuth nitrate complexes with triethanolamine (TEA), sodium tellurosulfite, and sodium selenosulfite were used as precursor materials. The film was obtained at 55 ± 0.5 °C in an aqueous alkaline medium (pH = 10.5 ± 0.2). As-deposited film was characterized by chemical compositional, optical, and electrical analyses. The optical absorption spectrum for the sample was recorded in the wavelength region 400–900 nm. It shows a high coefficient of absorption (α = 105 cm–1) with an allowed direct type of transition. X-ray diffraction (XRD) study of the film shows a nanocrystalline and rhombohedral structure. From scanning electron microscopy (SEM), atomic force microscopy (AFM), and energy dispersive X-ray analysis (EDAX) studies, the deposited film shows uniform morphology and good stoichiometry. X-ray photoelectron spectroscopy (XPS) was used to study the binding energy and surface oxidation of the material. Electrical conduction study shows that material is an n-type semiconductor and shows good thermoelectric figure of merit.
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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".