MétaCan
Menu
Back to cohort

Conditions for high yield of selective-area epitaxy InAs nanowires on SiO<sub><i>x</i></sub>/Si(111) substrates

2015· article· en· W1896607265 on OpenAlexafffund
Mitchell Robson, В. Г. Дубровский, Ray LaPierre

Bibliographic record

VenueNanotechnology · 2015
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaRussian Foundation for Basic Research
KeywordsMaterials scienceNanowireNucleationMolecular beam epitaxyYield (engineering)EpitaxyCrystalliteSubstrate (aquarium)Flux (metallurgy)SemiconductorOptoelectronicsNanotechnologyCrystallographyChemical engineeringLayer (electronics)Composite materialMetallurgyChemistry

Abstract

fetched live from OpenAlex

Experimental data and a model are presented which define the boundary values of V/III flux ratio and growth temperature for droplet-assisted nucleation of InAs semiconductor nanowires in selective-area epitaxy on SiO(x)/Si (111) substrates by molecular beam epitaxy. Within these boundaries, the substrate receives a balanced flux of group III and V materials allowing the growth of vertically oriented nanowires as compared to the formation of droplets or crystallites.

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 score0.033
Threshold uncertainty score0.876

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 head0.021
GPT teacher head0.229
Teacher spread0.208 · 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

Citations25
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueNanotechnologySame topicNanowire Synthesis and ApplicationsFrench-language works237,207