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Record W3010517268 · doi:10.1364/osac.386533

Photosensitised PDMS for femtosecond laser writing

2020· article· en· W3010517268 on OpenAlexafffund
Jean-Sébastien Boisvert, A. R. Hlil, Iden Hassan, Jyothis Thomas, Pierre Lorre, Wagner Correr, Yannick Ledemi, Younès Messaddeq, Raman Kashyap

Bibliographic record

VenueOSA Continuum · 2020
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsUniversité LavalPolytechnique Montréal
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Excellence Research Chairs, Government of CanadaCanada Foundation for Innovation
KeywordsMaterials scienceFemtosecondLaserPhotonicsSiloxaneRaman spectroscopyRefractive indexOptoelectronicsMulti-mode optical fiberOpticsPolymerOptical fiberComposite material

Abstract

fetched live from OpenAlex

This work demonstrates a new photosensitive glassy material in the form of poly-di-methyl-siloxane (PDMS) loaded with novel Ge-derivatives. A femtosecond laser is used to write directly into the bulk of pristine and Ge-modified PDMS. Raman spectroscopy is used to study the origin of the stable refractive index (RI) change induced by fs laser exposure. Multimode waveguides, as well as a highly tunable diffraction gratings, were written into the bulk of the new material, Ge-PDMS, in order to demonstrate the inclusion of photonics structures embedded inside. Novel photonics functionality may now be incorporated into PDMS, which is a material widely used in the optics industry and for lab-on-chip application (LOC).

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 score0.006
Threshold uncertainty score0.021

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)0.0060.002

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 head0.014
GPT teacher head0.205
Teacher spread0.191 · 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".

Quick stats

Citations12
Published2020
Admission routes2
Has abstractyes

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