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Record W4405010328 · doi:10.1038/s41598-024-81731-1

On chip glucose sensing using guided waves at terahertz frequencies

2024· article· en· W4405010328 on OpenAlexafffund
Mohsen Haghighat, Thomas E. Darcie, Levi Smith

Bibliographic record

VenueScientific Reports · 2024
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaSimon Fraser UniversityUniversity of VictoriaUniversity of Ottawa
KeywordsTerahertz radiationAttenuation coefficientPermittivityMaterials scienceOptoelectronicsSilicon nitrideAbsorption (acoustics)Coplanar waveguideAttenuationPhysicsOpticsSiliconDielectricMicrowave

Abstract

fetched live from OpenAlex

This paper demonstrates an on-chip anhydrous D-glucose sensor using a coplanar stripline (CPS) on a thin (1 [Formula: see text]m) silicon nitride membrane at terahertz (THz) frequencies. A thin layer (≈ 10 [Formula: see text]m) of D-glucose was placed in close proximity to the CPS and the transmission response was measured using a modified THz-TDS setup. The D-glucose introduces frequency-dependent changes to the effective permittivity of the CPS resulting in a modified spectral response at the receiver. Measurement results show absorption signatures at 1.42 THz and 2.07 THz corresponding to the first two significant resonances beyond 1 THz for D-glucose allowing for label-free detection. The frequency-dependent attenuation coefficient was estimated by simulation for several D-glucose layer thicknesses using a modified Lorentz model. Measurement results align with simulations and other literature that use free-space THz radiation. This work verifies on-chip THz sensing of D-glucose and presents a pathway toward on-chip sensing of other materials at THz frequencies.

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 score0.309
Threshold uncertainty score0.542

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)0.0000.000

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 head0.022
GPT teacher head0.254
Teacher spread0.232 · 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

Citations8
Published2024
Admission routes2
Has abstractyes

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