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Resonant photo-thermal modification of vertical gallium arsenide nanowires studied using Raman spectroscopy

2016· article· en· W2353117977 on OpenAlexafffund
Jaspreet Walia, Jonathan Boulanger, Navneet Dhindsa, Ray LaPierre, Xiaowu Tang, Simarjeet S. Saini

Bibliographic record

VenueNanotechnology · 2016
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsMcMaster UniversityUniversity of Waterloo
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaIndustry CanadaCMC Microsystems
KeywordsNanowireMaterials scienceRaman spectroscopyGallium arsenideOptoelectronicsAbsorption (acoustics)SpectroscopyIndium arsenideNanotechnologyOpticsComposite material

Abstract

fetched live from OpenAlex

Gallium arsenide nanowires have shown considerable promise for use in applications in which the absorption of light is required. When the nanowires are oriented vertically, a considerable amount of light can be absorbed, leading to significant heating effects. Thus, it is important to understand the threshold power densities that vertical GaAs nanowires can support, and how the nanowire morphology is altered under these conditions. Here, resonant photo-thermal modification of vertical GaAs nanowires was studied using both Raman spectroscopy and electron microscopy techniques. Resonant waveguiding, and subsequent absorption of the excited optical mode reduces the irradiance vertical GaAs nanowires can support relative to horizontal ones, by three orders of magnitude before the onset of structural changes occur. A power density of only 20 W mm(-2) was sufficient to induce local heating in the nanowires, resulting in the formation of arsenic species. Upon further increasing the power, a hollow nanowire morphology was realized. These findings are pertinent to all optical applications and spectroscopic measurements involving vertically oriented GaAs nanowires. Understanding the optical absorption limitations, and the effects of exceeding these limitations will help improve the development of all III-V nanowire devices.

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 score0.024
Threshold uncertainty score0.492

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 head0.020
GPT teacher head0.254
Teacher spread0.234 · 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

Citations9
Published2016
Admission routes2
Has abstractyes

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