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Record W2511134212 · doi:10.1063/1.4961680

Molecular beam epitaxy growth of Al-rich AlGaN nanowires for deep ultraviolet optoelectronics

2016· article· en· W2511134212 on OpenAlexaff
Songrui Zhao, Steffi Y. Woo, Sharif Sadaf, Yuanpeng Wu, Alexandre Pofelski, David Laleyan, Roksana Tonny Rashid, Yongjie Wang, Gianluigi A. Botton, Zetian Mi

Bibliographic record

VenueAPL Materials · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsMcMaster UniversityMcGill University
Fundersnot available
KeywordsMolecular beam epitaxyMaterials scienceNanowireOptoelectronicsUltravioletLight-emitting diodeEpitaxySubstrate (aquarium)Ternary operationWavelengthWide-bandgap semiconductorNanotechnologyLayer (electronics)

Abstract

fetched live from OpenAlex

Self-organized AlGaN nanowires by molecular beam epitaxy have attracted significant attention for deep ultraviolet optoelectronics. However, due to the strong compositional modulations under conventional nitrogen rich growth conditions, emission wavelengths less than 250 nm have remained inaccessible. Here we show that Al-rich AlGaN nanowires with much improved compositional uniformity can be achieved in a new growth paradigm, wherein a precise control on the optical bandgap of ternary AlGaN nanowires can be achieved by varying the substrate temperature. AlGaN nanowire LEDs, with emission wavelengths spanning from 236 to 280 nm, are also demonstrated.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.007
GPT teacher head0.234
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), 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

Citations75
Published2016
Admission routes1
Has abstractyes

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