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Record W2035474383 · doi:10.1063/1.1484554

Molecular-beam epitaxial growth of GaAs and InGaAs/GaAs nanodot arrays using anodic Al2O3 nanohole array template masks

2002· article· en· W2035474383 on OpenAlexaff
Xingao Mei, D. Kim, Harry E. Ruda, Qixin Guo

Bibliographic record

VenueApplied Physics Letters · 2002
Typearticle
Languageen
FieldMaterials Science
TopicAnodic Oxide Films and Nanostructures
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNanodotQuantum dotCathodoluminescenceMaterials scienceMolecular beam epitaxyOptoelectronicsHeterojunctionGallium arsenideEpitaxyNanotechnologyLuminescenceLayer (electronics)

Abstract

fetched live from OpenAlex

Highly ordered arrays of nanosized GaAs-based dots were successfully prepared on GaAs (001) substrates by molecular-beam epitaxy using selected area growth. Selected area growth employed alumina nanochannel array (NCA) templates formed by anodic oxidation, bonded to the GaAs substrates. Homogeneous GaAs dots, as well as compositionally modulated heterostructures within the nanosized dots, were demonstrated. In the latter case, multilayer InGaAs/GaAs heterostructured nanodot arrays were fabricated. Dot growth occurred only as defined by the template mask, resulting in a hexagonal lattice of dots with 100 nm period spacing, with dots retaining the circular lateral shape of the pores as determined by the NCA template pore size; dot diameters were adjustable from 45 to 85 nm for a lattice period of 100 nm. Cathodoluminescence spectra from an InGaAs/GaAs 10×10 dot array clearly showed an emission peak at 920 nm (5 K), confirming the formation of a high-quality InGaAs/GaAs quantum dot array.

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)0.000
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 score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.015
GPT teacher head0.209
Teacher spread0.194 · 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

Citations126
Published2002
Admission routes1
Has abstractyes

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