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Record W2906439934 · doi:10.1039/c8nr06553e

Antireflective structures on highly flexible and large area elastomer membrane for tunable liquid-filled endoscopic lens

2018· article· en· W2906439934 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNanoscale · 2018
Typearticle
Languageen
FieldEngineering
TopicElectrowetting and Microfluidic Technologies
Canadian institutionsKootenay Association for Science & Technology
FundersNational Research Foundation of Korea
KeywordsAnti-reflective coatingMaterials scienceElastomerLens (geology)MembraneNanotechnologyComposite materialOpticsChemistryPhysics

Abstract

fetched live from OpenAlex

The antireflection coating on an optical lens plays a key role not only in minimizing specular reflection but also in maximizing light transmission. Antireflective structures (ARS) found in the eyes of moths have the same role as conventional antireflection coating, and they also provide many intriguing features such as broadband coverage, self-antireflection, and strong water repellence. In particular, ARS on a highly flexible membrane can effectively deliver antireflective properties, which are rarely achieved by conventional hard coating. Herein, we report antireflective structures on a highly flexible elastomeric lens membrane for tunable endoscopic imaging applications. A thin antireflective membrane was fabricated using a large-area nanohole template and replica molding. The thin membrane increases light transmittance up to 96.8% in the visible region while enhancing the image contrast up to 56%, higher than that of a smooth membrane during lens deformation. This antireflective, tunable, liquid-filled lens offers new opportunities for compact endoscopic laparoscopy enabling maximum transmittance and variable zoom imaging in narrow and low-illumination environments.

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.

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 score0.052
Threshold uncertainty score0.727

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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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