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Record W4285089683 · doi:10.3390/catal12070771

Heterogeneous Nanoplasmonic Amplifiers for Photocatalysis’s Application: A Theoretical Study

2022· article· en· W4285089683 on OpenAlexaff
Chawki Awada, Thameur Hajlaoui, Noura Al Suliman, Chahinez Dab

Bibliographic record

VenueCatalysts · 2022
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversité du Québec à RimouskiUniversité de Sherbrooke
FundersKing Faisal University
KeywordsMaterials scienceNanotechnologySurface plasmon resonancePlasmonSiliconAntenna (radio)OptoelectronicsNanoparticleSilicon dioxideSilicon nanowiresComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

The higher cost of Ag and Au and their resonance frequency shift limitation opened the way to find an alternative solution by developing new nanohybrid antenna based on silicon and silicon dioxide coated with metallic nanoparticles. The latter has been recently solicited as a promising configuration for more large-scale plasmonic utilisation. This work reports a multitude of fascinating new phenomenon on LSPR on silicon antenna wires coated with core-shell nanospheres and the studying of the nanoplasmonics amplifiers to control optical and electromagnetic properties of materials. The LSPR modes and their interaction with the silicon nanowires are studied using numerical methods. The suggested configuration offers resonance covering the UV-visible and NIR regions, making them an adaptable addition to the nanoplasmonics toolbox.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.011
GPT teacher head0.249
Teacher spread0.238 · 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 designSimulation or modeling
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

Citations4
Published2022
Admission routes1
Has abstractyes

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