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Record W2133619288 · doi:10.1109/isot.2010.5687333

Nano-fabrication dependent quality factor in photonic crystal slab biosensors

2010· article· en· W2133619288 on OpenAlexaff
Hooman Akhavan, Mohamed El-Beheiry, Ofer Levi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFabricationBiosensorPhotonic crystalMaterials scienceFluidicsOptoelectronicsQ factorResonatorSensitivity (control systems)Refractive indexOpticsNanotechnologyPhysicsElectronic engineering

Abstract

fetched live from OpenAlex

Photonic crystal slabs (PCS) are attractive for label-free optical bio-sensors inside micro-fluidic portable diagnostic systems due to their high sensitivity and easy coupling to external radiation. Obtaining high quality factor (Q) values for the guided resonances in these index-of-refraction PCS biosensors is crucial for high sensitivity. Non-ideal fabrication of the hole array in the PCS due to electron beam writing, pattern transfer, and reactive ion etching (RIE) steps will result in imperfect circular hole shapes, and non vertical hole profile that can reduce the Q values. We evaluate the effect of nano-fabrication on the quality factor of guided resonances in PCS biosensors and investigate the potential limitations on sensitivity with current fabrication technologies in a realistic PCS biosensor due to fabrication errors. Spectral broadening of the guided resonances (lower Q values) is found for the fundamental guided resonance modes but no significant changes were observed in higher order guided resonances. These fin dings are consistent with reduced bio-sensing sensitivity in higher order modes due to reduced field overlap with the analyte in side the micro-fluidic channels.

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 categoriesInsufficient payload (model declined to judge)
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 score0.256
Threshold uncertainty score0.997

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.291
Teacher spread0.275 · 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.

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

Citations3
Published2010
Admission routes1
Has abstractyes

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