MétaCan
Menu
Back to cohort
Record W2889167425 · doi:10.1002/jrs.5473

Near‐field enhancements and surface plasmon polaritons with multifunctional oxide thin films

2018· article· en· W2889167425 on OpenAlexafffund
Chahinez Dab, Reji Thomas, Thameur Hajlaoui, Andreas Ruëdiger

Bibliographic record

VenueJournal of Raman Spectroscopy · 2018
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsUniversité de SherbrookeInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsMaterials scienceRaman spectroscopySurface plasmon polaritonPlasmonPolaritonOptoelectronicsSurface plasmonBarium titanateSubstrate (aquarium)OpticsThin filmSurface-enhanced Raman spectroscopyElectromagnetic fieldNanotechnologyDielectricRaman scattering

Abstract

fetched live from OpenAlex

Abstract The thickness of multifunctional oxide films directly affects the localized enhancement of the electromagnetic field and hence is a key factor for realizing novel photonic or optoelectronic devices. To this end, we theoretically exploit the principle of tip‐enhanced Raman spectroscopy on the surface of multifunctional oxide films (bismuth ferrite and barium titanate) on a gold substrate. An electromagnetic field enhancement of up to 10 4 in close proximity of the tip apex was obtained. The good agreement between simulation and experiment of spatial resolution of the tip supports the validity of our model. By investigation of surface plasmon polaritons that propagates at the interface between the multifunctional film and the gold substrate, we demonstrated a thickness dependent propagation length and amplitude. This study indicates a critical thickness of the films above which neither a considerable near‐field nor a tip‐mediated excitation are observed. This confirms the validity, promise, and power of tip‐enhanced Raman spectroscopy technique for the analysis of various electro‐optic materials.

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 score0.087
Threshold uncertainty score0.591

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 integrity0.0000.001
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 head0.008
GPT teacher head0.247
Teacher spread0.239 · 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

Citations2
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Raman SpectroscopySame topicPlasmonic and Surface Plasmon ResearchFrench-language works237,207