Photocorrosion metrology of photoluminescence emitting GaAs/AlGaAs heterostructures
Bibliographic record
Abstract
Abstract High sensitivity of the photoluminescence (PL) effect to surface states and chemical reactions on surfaces of PL emitting semiconductors has been attractive in monitoring photo-induced microstructuring of such materials. To address the etching at nano-scale removal rates, we have investigated mechanisms of photocorrosion of GaAs/Al 0.35 Ga 0.65 As heterostructures immersed either in deionized water or aqueous solution of NH 4 OH and excited with above-bandgap radiation. The difference in photocorrosion rates of GaAs and Al 0.35 Ga 0.65 As appeared weakly dependent on the bandgap energy of these materials, and the intensity of an integrated PL signal from GaAs quantum wells or a buried GaAs epitaxial layer was found dominated by the surface states and chemical reactivity of heterostructure surfaces revealed during the photocorrosion process. Under optimized photocorrosion conditions, the method allowed resolving a 1 nm thick GaAs sandwiched between Al 0.35 Ga 0.65 As layers. We demonstrate that this approach can be used as an inexpensive, and simple room temperature tool for post-growth diagnostics of interface locations in PL emitting quantum wells and other nano-heterostructures.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".