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Record W2941467555 · doi:10.1039/c9nr01262a

Structural origin of the high-performance light-emitting InGaN/AlGaN quantum disks

2019· article· en· W2941467555 on OpenAlexafffund
Shaobo Cheng, Brian Langelier, Yong‐Ho Ra, Roksana Tonny Rashid, Zetian Mi, Gianluigi A. Botton

Bibliographic record

VenueNanoscale · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsMcGill UniversityMcMaster UniversityCanadiana.org
FundersDivision of Electrical, Communications and Cyber SystemsNatural Sciences and Engineering Research Council of CanadaMcMaster UniversityNational Science Foundation
KeywordsMaterials scienceOptoelectronicsQuantumLight-emitting diodePhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

Ternary III-nitride-based nanowires with highly efficient light-emitting properties are essential for a broad range of applications. By using the selective area molecular-beam epitaxy method, InGaN/AlGaN quantum disks (QDs) embedded in hexagonal GaN nanowires were successfully grown. With the help of atomic-scale-resolved transmission electron microscopy and atom probe tomography, atomic ordering and other related structural information, such as crystallography and local chemistry, have been unambiguously revealed to provide unique insights into the exceptionally strong photoluminescence enhancements. A boomerang-shaped InGaN/AlGaN QD was identified, and atomic-level 1 : 1 periodic chemical ordering within the boomerang shaped AlGaN layers along the c-direction was revealed, confirming the preferential site occupation of Al-atoms. This type of growth provides a strong suppression of the quantum-confined Stark effect and is thus likely a very strong contributor to the exceptional properties. This work therefore enables us to directly establish the key structural elements necessary to understand the exceptionally strong emission exhibited by these materials. Optimization of the configurations of QDs could be an alternative design tool for developing various advanced LED device applications with well-designed structure and desirable optical properties.

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 score0.272
Threshold uncertainty score0.585

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)0.0010.000

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 head0.011
GPT teacher head0.232
Teacher spread0.222 · 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

Citations18
Published2019
Admission routes2
Has abstractyes

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