Effect of Thickness on Structural, Morphological, and Optical Properties of Copper (Cu) Doped Zinc Selenide (ZnSe) Thin Films by Vacuum Evaporation Method
Bibliographic record
Abstract
Effect of thickness on structural, optical and morphological properties of 2% copper (Cu) doped zinc selenide (ZnSe) thin films, grown onto chemically and ultrasonically cleaned glass substrate by thermal evaporation method in high vacuum (~10-6 Torr) were studied. Films of 100, 200, 300 and 400 nm thickness were prepared at 200℃ substrate temperature where annealing temperature and annealing time was fixed at 100℃ and 1 hour respectively. The X-ray diffraction (XRD) exhibited polycrystalline nature indicating the zinc-blende structure with a preferential orientation along the (111) plane of cubic phase. The grain size was found to be 19.27 nm. Dislocation density and microstrain were also found as 2.691 × 10-3 nm-2 and 1.85 × 10-3 respectively. Atomic Force Microscopy (AFM) study confirmed the growth of grains and their distribution over the entire surface of the films. All the films were characterized optically by UV-VIS-NIR spectrophotometer in the photon wavelength ranging from 300 to 1000 nm. The optical transmittance and reflectance were utilized to compute the absorption coefficient, extinction coefficient and band gap energy of the films. The calculated band gap energy was found to increase (2.99 to 3.94 ev) with varying thickness. The maximum transmittance was found to be 87.65% for the 400 nm film. Journal of Bangladesh Academy of Sciences, Vol. 43, No. 2, 159-168, 2019
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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".