Photoluminescence Monitored Sustainable Digital Photocorrosion of GaAs/Al<sub>0.35</sub>Ga<sub>0.65</sub>As Quantum Well Microstructures
Bibliographic record
Abstract
Digital photocorrosion (DIP) of GaAs/AlGaAs nanoheterostructures is an attractive method for detecting surface‐immobilized electrically charged biomolecules such as bacteria. The process is normally carried out in ammonia‐ or phosphate‐buffered saline and monitored in situ to reveal photoluminescence (PL) intensity maximum (PL max ) when the photocorrosion front crosses the GaAs‐AlGaAs interface. The temporal position of PL max plotted as a function of the concentration of surface‐immobilized biomolecules allows calibration of the process and detection of unknown concentrations of bacteria. Successive employment of numerous GaAs‐AlGaAs interfaces in a stack of GaAs/AlGaAs quantum wells (QWs) for biosensing is drastically restricted due to the diminishing PL intensity related to accumulation of Al oxides and other byproducts on the surface of processed samples. Herein, the application of a cyclic injection of NaOH solution for chemical “sweeping” of the AlGaAs surface to maintain a sustainable DIP process manifested by nonvanishing amplitude of the PL signal is reported. The successful measurement of eleven PL max with comparable amplitudes from the same GaAs/AlGaAs QW microstructure paves the way to the development of an advanced biochip delivering a large number of data points.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".