Formation of gallium arsenide nanostructures in Pyrex glass
Bibliographic record
Abstract
In this paper, we report on a simple, low-cost process to grow GaAs nanostructures of a few nm diameter and ∼50 nm height in Pyrex glass wafers. These nanostructures were grown by sequential plasma activation of GaAs and Pyrex glass surfaces using a low-temperature hybrid plasma bonding technology in air. Raman analyses of the activated surfaces show gallium oxide and arsenic oxide, as well as suppressed non-bridging oxygen with aluminate and boroxol chains in glass. The flow of alkaline ions toward the cathode and the replacement of alkaline ions by Ga and As ions in glass result in the growth of GaAs nanostructures in nanopores/nanoscratches in glass. These nanopores/nanoscratches are believed to be the origin of the growth of the nanostructures. It was found that the length of the GaAs nanostructures may be controlled by an electrostatic force. Cross-sectional observation of the bonded interface using high-resolution transmission electron microscopy confirms the existence of the nanostructures. A possible application of the nanostructures in glass is a filtration system for biomolecules.
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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) | 0.000 | 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 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".