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Record W3155474415 · doi:10.1364/oe.424414

Enhanced on-chip terahertz vibrational absorption spectroscopy using evanescent fields in silicon waveguide structures

2021· article· en· W3155474415 on OpenAlexafffund
Hadi Amarloo, Safieddin Safavi‐Naeini

Bibliographic record

VenueOptics Express · 2021
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaC-COM Satellite Systems
KeywordsTerahertz radiationMaterials scienceWaveguideTerahertz spectroscopy and technologyOpticsDielectricSpectroscopyOptoelectronicsSiliconAbsorption (acoustics)Physics

Abstract

fetched live from OpenAlex

In this study, we demonstrate on-chip terahertz absorption spectroscopy using dielectric waveguide structures. The structures' evanescent fields interact with the sample material surrounding the waveguide, enabling the absorption signature of the material to be captured. The ability of fabricated terahertz dielectric waveguide structures, based on the newly developed silicon-BCB-quartz platform, to capture the fingerprint of α-lactose powder (as an example material) at 532 GHz is examined. Enhancement of the spectroscopy sensitivity through techniques such as tapering the waveguide, confining the field in a slot dielectric waveguide, and increasing the interaction length using a spiral-shaped waveguide are investigated experimentally. The proposed on-chip spectroscopy structures outperform conventional and state-of-the-art approaches in terms of sensitivity and compactness.

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 score0.047
Threshold uncertainty score0.544

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 head0.013
GPT teacher head0.254
Teacher spread0.241 · 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

Citations32
Published2021
Admission routes2
Has abstractyes

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