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Record W1965761374 · doi:10.1063/1.4773206

Effects of Be doping on InP nanowire growth mechanisms

2012· article· en· W1965761374 on OpenAlexaff
R. Yee, S. J. Gibson, В. Г. Дубровский, Ray LaPierre

Bibliographic record

VenueApplied Physics Letters · 2012
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDopantNanowireNucleationDopingMaterials scienceMolecular beam epitaxyMonolayerDiffusionChemical physicsVapor–liquid–solid methodNanotechnologyEpitaxyCondensed matter physicsOptoelectronicsLayer (electronics)ChemistryThermodynamics

Abstract

fetched live from OpenAlex

Be-doped InP nanowires were grown by the gold-assisted vapour-liquid-solid mechanism in a gas source molecular beam epitaxy system. The InP nanowire length versus diameter [L(D)] dependence revealed an unexpected transition with increasing Be dopant concentration. At Be dopant concentration below ∼1018 cm−3, nanowires exhibited the usual inverse L(D) relationship, indicating a diffusion-limited growth regime. However, as dopant concentration increased, the nanowire growth rate was suppressed for small diameters, resulting in an unusual L(D) dependence that increased before saturating in height at about 400 nm. The cause of this may be a change in the droplet chemical potential, introducing a barrier to island nucleation. We propose a model accounting for the limitations of diffusion length and monolayer nucleation to explain this behaviour.

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)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.186
Teacher spread0.179 · 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

Citations26
Published2012
Admission routes1
Has abstractyes

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