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Record W4402810472 · doi:10.1021/acs.cgd.4c00814

Molecular Beam Epitaxial Growth and Characterization of Nanoscale ScGaN

2024· article· en· W4402810472 on OpenAlexafffund
Mohammad Fazel Vafadar, Milad Fathabadi, Songrui Zhao

Bibliographic record

VenueCrystal Growth & Design · 2024
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
KeywordsCharacterization (materials science)Nanoscopic scaleMaterials scienceNanotechnologyMolecular beam epitaxyEpitaxyCrystallographyChemistry

Abstract

fetched live from OpenAlex

Low-dimensional semiconductor materials, including nanowires, have been an attractive platform for cutting-edge semiconductor device development. On the other hand, scandium (Sc) containing III-nitrides (Sc–III-nitrides) is an emerging material system, offering not only novel ferroelectric devices but also potentially multifunctional devices in a single-material platform. In this study, we investigate nanoscale Sc x Ga 1– x N (ScGaN) hosted in GaN nanowires grown by molecular beam epitaxy on Si substrate. The major findings are (1) Within each ScGaN insert layer, the Sc content is not uniform as indicated by transmission electron microscopy studies, suggesting the formation of ScGaN nanoclusters with different Sc contents; (2) ScGaN shell is formed spontaneously; and (3) Zincblende phase is observed in the ScGaN insert layers although the estimated average Sc content is only around x = 0.16. The possible mechanisms related to these findings are also discussed. These unveiled correlated epitaxial and structural properties could help in the development of Sc–III-nitride nanowire devices.

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 score0.034
Threshold uncertainty score0.632

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 head0.010
GPT teacher head0.216
Teacher spread0.206 · 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

Citations5
Published2024
Admission routes2
Has abstractyes

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