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Record W3165031703 · doi:10.1021/acs.cgd.1c00327

Molecular Beam Epitaxial Growth of AlN Thin Films on Si through Exploiting Low Al Adatom Migration and the Nitrogen-Rich Environment on a Nanowire Template

2021· article· en· W3165031703 on OpenAlex
Xue Yin, Qihua Zhang, Songrui Zhao

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCrystal Growth & Design · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceMolecular beam epitaxyThin filmNanowireNitrideOptoelectronicsEpitaxyGallium nitrideElectron diffractionLayer (electronics)DiffractionGalliumEtching (microfabrication)AluminiumUltravioletReflection (computer programming)NanotechnologyOpticsComposite materialMetallurgy

Abstract

fetched live from OpenAlex

In this work, we demonstrate an aluminum nitride (AlN) thin film on Si through exploiting the low Al adatom migration and the nitrogen (N)-rich environment on a nanowire template by molecular beam epitaxy. The AlN thin film is relatively smooth, and the X-ray diffraction experiments further suggest that the film is nearly strain free. In addition, the observation of 3 × 3 reconstruction from the reflection high-energy electron diffraction suggests that the AlN film is N-polar, which is further confirmed by chemical etching experiments. We further show that, using such an AlN thin film as a buffer layer, room-temperature ultraviolet-emitting aluminum gallium nitride (AlGaN) epilayers at various wavelengths can be obtained on Si.

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.

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 score0.013
Threshold uncertainty score0.895

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 head0.015
GPT teacher head0.215
Teacher spread0.200 · 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