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Record W7132945907

Electromagnetic simulations of nanooptics based on the Finite Difference Time Domain (FDTD) method

2007· dissertation· W7132945907 on OpenAlexaff
Toan Trung Nguyen

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsBank of CanadaLibrary and Archives Canada
Fundersnot available
KeywordsDielectricSurface plasmon polaritonSurface plasmonFinite-difference time-domain methodOpacityPlasmonPolarization (electrochemistry)Electromagnetic radiationAperture (computer memory)Coupling (piping)
DOInot available

Abstract

fetched live from OpenAlex

Electrodynamic simulations based on the Finite Difference Time Domain (FDTD) method were used to investigate the transmission properties of periodic nanohole arrays in opaque metal films surrounded by dielectric media. It is believed that the mechanism for extraordinary transmission through these nanoarrays involves the coupling of evanescent Surface Plasmon Polariton (SPP) fields to the momentum of the array. Theoretical calculations performed show that transmission peak positions depend on the periodicity (separation) of the holes and changes in the surrounding dielectric environment. Additionally, polarization effects, unconventional aperture shapes and interactions between localized surface plasmons of individual apertures were analyzed. The combination of surface plasmon generated fields, their sensitivity to contacting dielectric medium, and the tunable properties of these periodic arrays provides insight into the potential design of novel chemical biosensors.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.337
Teacher spread0.316 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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