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Record W2342250508 · doi:10.1149/ma2016-01/42/2110

(Invited) GaAs Quantum Dots in Gap Nanowires: Growth and Luminescence

2016· article· en· W2342250508 on OpenAlexaff
Ray LaPierre, P Kuyanov, Jonathan Boulanger

Bibliographic record

VenueECS Meeting Abstracts · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNanowireMaterials scienceQuantum dotHeterojunctionOptoelectronicsPhotoluminescenceMolecular beam epitaxyNanotechnologyLuminescencePassivationDiodeLight-emitting diodeEpitaxy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.245
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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