MétaCan
Menu
Back to cohort
Record W2004051951 · doi:10.1117/12.545923

Optical properties of porous helical thin films and the effects of post-deposition annealing

2004· article· en· W2004051951 on OpenAlexafffund
Andy C. van Popta, Jeremy C. Sit, Michael J. Brett

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Typearticle
Languageen
FieldMaterials Science
TopicOptical Coatings and Gratings
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceThin filmAnnealing (glass)CrystalliteRefractive indexPorosityRutileDielectricPhysical vapor depositionAnataseDeposition (geology)OpticsOptoelectronicsNanotechnologyComposite materialChemical engineeringMetallurgy

Abstract

fetched live from OpenAlex

Porous thin films have been fabricated by physical vapor deposition at an extremely oblique angle of incidence (85°). This deposition technique, called glancing angle deposition (GLAD), was used to create thin films composed of isolated helical columns. By investigating a variety of dielectrics, we found that helical GLAD films fabricated from titanium dioxide produce the strongest chiral optical response because of its large refractive index. Further improvements were made by using post-deposition annealing to form anatase and rutile polycrystalline phases of TiO<sub>2</sub>. By tailoring the pitch of the helical structures, the circular Bragg reflection band was tuned to preferentially reflect red, green, and blue light. The high porosity of a GLAD film (>50%) permits liquid crystals (LC) to be incorporated into the pores of the helical nanostructure, which creates chiral alignment in otherwise non-chiral LCs. This technique improves circular Bragg reflection and can create addressable hybrid materials with potential applications to high-efficiency reflective displays.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.320
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.209
Teacher spread0.202 · 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

Citations19
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicOptical Coatings and GratingsFrench-language works237,207