(Invited) GaAs Quantum Dots in Gap Nanowires: Growth and Luminescence
Bibliographic record
Abstract
Nanowires are rod or whisker-like structures with length on the order of microns and diameter from tens to hundreds of nanometers. They represent a new class of three-dimensional materials, and the next step in the evolution of conventional two-dimensional thin films, quantum wells, or heterostructures. Nanowires are typically fabricated by the assistance of foreign metal catalysts, such as Au, that collect deposited material, resulting in localized growth of nanowires. However, the use of foreign metal particles can result in contamination of the nanowires and reduction in the carrier lifetime, which degrades device performance. In the present work, we present the self-assisted growth of GaP nanowires by molecular beam epitaxy, using Ga droplets as a seed particle without the use of any foreign metal catalysts. Growth of the nanowire occurs by selective-area epitaxy using a patterned array of holes in an SiO x mask. The holes collect Ga adatoms forming a Ga droplet that seeds the nanowire growth. The size of the Ga droplet can be controlled by a novel evaporation process, resulting in ultra-thin nanowire structures. GaAs heterostructures were introduced into the GaP nanowires during growth resulting in quantum dots. The quantum dots are encapsulated in GaP, resulting in passivation of the QD surfaces. Photoluminescence emission was observed from the QDs in the visible range. The emission wavelength is tunable by the size or composition of the QDs. This process results in controlled luminescence emission with application in single photon sources, light emitting diodes, or laser diodes.
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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".