Synthesis Porous GaN by Using UV-assisted Electrochemical Etching and Its Optical Studies
Bibliographic record
Abstract
The PL of porous GaN sample shows higher intensity with smaller FWHM and red-shifting relative to the as-grown sample. The energy gap for porous GaN sample was smaller compare to the as-grown sample. The SEM surface image of UV-assisted electrochemical etching process is shown a shape and size of pore which was formed on the surface of the GaN, therefore the shape of pores formed was in spherical shape. The size of the pores formed has diameter as small as 85 nm. Two PL peaks were observed in the as-grown and porous GaN sample. For the as-grown GaN, the higher peak was observed at “361.946 nm” and the other at “723.739 nm” which is in UV and red luminescence region respectively. The FWHM is “8.198 nm” at “361.946 nm”. For the porous GaN, the higher peak was observed at “364.235 nm” and at “728.039 nm”, so their FWHM are “4.244 nm” and “8.926 nm” respectively. The peaks of porous sample were red-shifted at “2.289 nm and 4.30 nm” respectively compare to the peaks of the as-grown GaN. PL intensity of the porous samples was observed to be increased. Raman peaks representative to the wurtzite GaN crystal, namely E2 (low) at 142.426 cm-1, E2 (high) at 568.771 cm-1, and A1 (LO) at 736.769 cm-1 were clearly observed.
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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".