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Highly ordered vertical GaAs nanowire arrays with dry etching and their optical properties

2014· article· en· W2092589215 on OpenAlex
Navneet Dhindsa, A. C. E. Chia, Jonathan Boulanger, Iman Khodadad, Ray LaPierre, Simarjeet S. Saini

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNanotechnology · 2014
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsMcMaster UniversityUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceNanowireEtching (microfabrication)OptoelectronicsGallium arsenideFabricationAbsorption (acoustics)Dry etchingAspect ratio (aeronautics)OpticsNanotechnologyComposite materialLayer (electronics)

Abstract

fetched live from OpenAlex

We report fabrication methods, including metal masks and dry etching, and demonstrate highly ordered vertical gallium arsenide nanowire arrays. The etching process created high aspect ratio, vertical nanowires with insignificant undercutting from the mask, allowing us to vary the diameter from 30 nm to 400 nm with a pitch from 250 nm to 1100 nm and length up to 2.2 μm. A diameter to pitch ratio of ∼68% was achieved. We also measured the reflectance from the nanowire arrays and show experimentally diameter-dependent strong absorption peaks resulting from resonant optical mode excitations within these nanowires. The reflectance curves match very well with simulations. The work done here paves the way towards achieving high efficiency solar cells and tunable photodetectors using III-V nanowires.

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.

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 score0.137
Threshold uncertainty score0.523

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 head0.007
GPT teacher head0.172
Teacher spread0.165 · 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