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Record W2606317553 · doi:10.1021/acs.jpcc.7b02039

Dendritic Plasmonics for Mid-Infrared Spectroscopy

2017· article· en· W2606317553 on OpenAlexafffund
Gregory Q. Wallace, Hayden Foy, Scott M. Rosendahl, François Lagugné‐Labarthet

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2017
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsCanadian Light Source (Canada)Western University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsPlasmonInfraredMaterials scienceInfrared spectroscopySpectroscopySurface plasmonNanostructureAbsorption (acoustics)Electron-beam lithographyLocalized surface plasmonSurface plasmon resonanceOptoelectronicsNear-infrared spectroscopyOpticsNanotechnologyChemistryNanoparticlePhysicsLayer (electronics)

Abstract

fetched live from OpenAlex

Metallic nanostructures that exhibit tailored optical resonances spanning from the near to mid-infrared spectral range are of particular interest for spectroscopic and optical measurements in these spectral domains that can benefit from localized surface-enhancement effects. Plasmon resonances shifted in the near or mid-infrared range could be used to further enhance the excitation and/or the emission of an optical process. Surface-enhanced infrared absorption (SEIRA) is one of such processes and can particularly benefit from plasmon-enhanced local fields yielding an increase in sensitivity toward the detection of an analyte. Herein, we have fabricated a series of gold dendritic nanostructures, prepared by electron-beam lithography, that exhibit plasmon resonances spanning the near and mid-infrared spectral regions. We explore the influence of the number of branches of the dendritic structures as well as the length of each generation together with the overall effect of the shape and symmetry on the resulting optical resonances. The creation of new resonances that appear upon newer fractal generation is explained in light of an hybridization model. Selected structures were then evaluated for SEIRA measurements toward an analyte.

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 score0.006
Threshold uncertainty score0.264

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 science0.0010.000
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 head0.018
GPT teacher head0.281
Teacher spread0.263 · 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

Citations40
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry CSame topicGold and Silver Nanoparticles Synthesis and ApplicationsFrench-language works237,207