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Record W1997234388 · doi:10.1364/josab.26.000279

Analysis of Bloch-surface-wave assisted diffraction-based biosensors

2009· article· en· W1997234388 on OpenAlexaff
Marco Liscidini, J. E. Sipe

Bibliographic record

VenueJournal of the Optical Society of America B · 2009
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDiffractionPhotonic crystalBiosensorDielectricGratingOpticsPolarization (electrochemistry)Materials scienceDiffraction efficiencyDiffraction gratingBloch waveRealization (probability)Dispersion (optics)Surface waveDispersion relationOptoelectronicsRefractive indexInfraredPhysicsNanotechnologyMathematicsCondensed matter physicsChemistry

Abstract

fetched live from OpenAlex

A systematic study of Bloch surface wave (BSW) properties and applications in diffraction-based biosensors is presented. The design of such devices starts with the calculation of the BSW dispersion relation for a semi-infinite one-dimensional photonic crystal. We propose an approach in which polarization and 1DPC termination effects are simply described. Since in a realistic device the number of periods is limited, we investigate the issues arising from finite size effects and the choice of a structure substrate. Diffraction efficiency is studied as a function index contrast, multilayer termination, grating thickness, and number of periods. Numerical examples for Si/SiO2 and a-Si1−xNx:H periodic dielectric stacks are presented, showing that BSW can be exploited for the realization of efficient diffraction-based biosensors from the infrared to the visible range.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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

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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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 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

Citations128
Published2009
Admission routes1
Has abstractyes

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Same venueJournal of the Optical Society of America BSame topicPhotonic and Optical DevicesFrench-language works237,207