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Record W2095718321 · doi:10.1186/1556-276x-9-255

Gold-silicon nanofiber synthesized by femtosecond laser radiation for enhanced light absorptance

2014· article· en· W2095718321 on OpenAlexaff
Abdul Salam Mahmood, Krishnan Venkatakrishnan, Bo Tan

Bibliographic record

VenueNanoscale Research Letters · 2014
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMaterials scienceFemtosecondLaserNanochemistryNanostructureSiliconOptoelectronicsSubstrate (aquarium)OpticsNanotechnologyNanoparticle

Abstract

fetched live from OpenAlex

In this study, we devised a new concept for the precise nanofabrication of Au-Si fibrous nanostructures using megahertz femtosecond laser irradiation in air and atmospheric pressure conditions. The weblike fibrous nanostructures of Au thin layer on silicon substrate, which are proposed for the application of solar cells, exhibit a specific improvement of the optical properties in visible wavelength. Varying numbers of laser interaction pulses were used to control the synthesis of the nanofibrous structures. Electron microscopy analysis revealed that the nanostructures are formed due to the aggregation of polycrystalline nanoparticles of the respective constituent materials with diameters varying between 30 and 90 nm. Measurement of the reflectance through a spectroradiometer showed that the coupling of incident electromagnetic irradiation was greatly improved over the broadband wavelength range. Lower reflectance intensity was obtained with a higher number of laser pulses due to the bulk of gold nanoparticles being agglomerated by the mechanism of fusion. This forms interweaving fibrous nanostructures which reveal a certain degree of assembly. PACS: 81.05.Zx; 81.07.-b.

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)0.001
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 score0.068
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.271
Teacher spread0.258 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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