DEPOSITION AND CHARACTERIZATION OF MAGNETRON CO-SPUTTERED InAlN FILM AT DIFFERENT Ar:N<sub>2</sub> GAS FLOW RATIOS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This work presents the influence of changing Ar:N 2 gas ratio on the growth and properties of InAlN films. InAlN films were deposited on [Formula: see text]-type Si(111) substrates by using magnetron co-sputtering method in 6:12, 10:10, 12:8 and 12:6 Ar:N 2 mixtures at 300[Formula: see text]C. The surface, structural, electrical and optical properties of the deposited films were evaluated at different Ar:N 2 ratios. The grain size and film thickness were increased by increasing the Ar flow with respect to N 2 . Structural characterization by X-ray diffraction (XRD) revealed an improvement in the crystalline quality of the [Formula: see text]-axis-oriented InAlN film by adjusting the Ar:N 2 ratio to 12:8, however no diffraction peak corresponding to InAlN was detected at 6:12 Ar:N 2 mixture. The surface roughness of InAlN film exhibited an increasing trend whereas the electrical resistivity of the film was decreased by increasing the Ar:N 2 ratio. The bandgap of InAlN film was calculated from the optical reflectance spectra and it was found to change by changing the Ar:N 2 gas ratio. The analysis of results from this work shows that the InAlN film with improved physical properties can be obtained through reactive magnetron co-sputtering method by adjusting the Ar:N 2 mixture to 12:8.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it