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Record W1997416513 · doi:10.1063/1.4894288

Gallium loading of gold seed for high yield of patterned GaAs nanowires

2014· article· en· W1997416513 on OpenAlexaff
Jonathan Boulanger, A. C. E. Chia, Ray LaPierre

Bibliographic record

VenueApplied Physics Letters · 2014
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNanowireEpitaxyMaterials scienceAnnealing (glass)Vapor–liquid–solid methodMolecular beam epitaxyGallium arsenideGalliumOptoelectronicsYield (engineering)Substrate (aquarium)NanotechnologyLayer (electronics)NanolithographyMetallurgyFabrication

Abstract

fetched live from OpenAlex

A method is presented for maximizing the yield and crystal phase purity of vertically aligned Au-assisted GaAs nanowires grown with an SiOx selective area epitaxy mask on GaAs (111)B substrates. The nanowires were grown by the vapor-liquid-solid (VLS) method in a gas source molecular beam epitaxy system. During annealing, Au VLS seeds will alloy with the underlying GaAs substrate and collect beneath the SiOx mask layer. This behavior is detrimental to obtaining vertically aligned, epitaxial nanowire growth. To circumvent this issue, Au droplets were pre-filled with Ga assuring vertical yields in excess of 99%.

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 score0.144
Threshold uncertainty score0.604

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 head0.193
Teacher spread0.183 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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