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Record W3006112930 · doi:10.22215/etd/2019-13826

Fabrication of Long Range Surface Plasmon Polariton Biosensors incorporating Optical Waveguides and Encapsulated Microfluidic Channels via Wafer Bonding"

2019· dissertation· en· W3006112930 on OpenAlexafffund
M. Salman Asif

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsCarleton University
FundersUniversity of Ottawa
KeywordsMaterials scienceFabricationWaferMicrofluidicsFluidicsSurface plasmon polaritonOptoelectronicsWafer bondingEtching (microfabrication)NanotechnologyPlasmonOpticsSurface plasmonLayer (electronics)Engineering

Abstract

fetched live from OpenAlex

A microfabricated structure incorporating optical waveguides and closed microfluidic channels is an essential component in realizing a practical long range surface plasmon polariton (LRSPP) biosensor.This has been achieved through advances in fabrication processes to realize reliable optical waveguides, and by development of a reliable wafer bonding process to create closed fluid channels.An existing process for fabrication of gold waveguides was modified by introducing ultra-shallow trenches to recess waveguides and present a planar surface for bonding.An improved fluidic channel etching process was characterized and successfully employed, yielding very smooth channel surfaces free from curtaining and grass issues.Optical performance of the complete bonded chips was demonstrated and verified using a cutback measurement method, producing an attenuation loss of 4.92 dB/mm.An alternative hot embossing process for formation of microfluidic channels on TOPAS substrate was investigated.Embossing die was produced on 4-inch silicon wafer using deep reactive ion etching (DRIE) to create 29 µm raised channels, and the die was subsequently used to transfer the channel structure to the TOPAS material.to work in the area of microfabrication in general, and in particular, optical LRSPP biosensor project.It was a fascinating introduction to the field, and an excellent opportunity to learn from their extensive knowledge and experience.It was a great pleasure to work under their supervision and directions.

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)0.000
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 score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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".

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Citations0
Published2019
Admission routes2
Has abstractyes

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