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Record W3175037050 · doi:10.1364/josab.420129

Surface plasmon resonance-based optical sensor using a thin layer of plasma

2021· article· en· W3175037050 on OpenAlexaff
Sofyan A. Taya, Noor E. Al-Ashi, Omar M. Ramahi, İlhami Çolak, I. S. Amiri

Bibliographic record

VenueJournal of the Optical Society of America B · 2021
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsUniversity of Waterloo
FundersArab Fund for Economic and Social Development
KeywordsSurface plasmon resonanceMaterials scienceRefractive indexLayer (electronics)PrismPlasmaAbsorption (acoustics)GrapheneSurface plasmonOptoelectronicsDielectricBiosensorChromiumOpticsPlasmonAnalytical Chemistry (journal)NanotechnologyChemistryComposite material

Abstract

fetched live from OpenAlex

We propose a surface plasmon resonance (SPR) biosensor that consists of six layers: glass prism (SF 10), chromium, metal, molybdenum disulphide, graphene, and sensing medium. A seventh layer is added between the glass prism and the chromium layer, which is a gap filled with plasma as a dielectric material. The plasma layer is expected to carry the amenity of the graphene optical characteristics and absorption ability. It is also expected to improve sensitivity of the SPR structure. The numerical calculations show that the sensitivity of the sensor is 76.11 deg/RIU (refractive index unit); without the plasma layer, it can be improved to 103 deg/RIU in the presence of 25 and 35 nm thick plasma and silver layers, respectively. The structure parameters are optimized with respect to the sensitivity. The proposed sensor can potentially be used for biological purposes.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.265
Teacher spread0.237 · 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 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

Citations60
Published2021
Admission routes1
Has abstractyes

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