MétaCan
Menu
Back to cohort
Record W4385484236 · doi:10.3390/nano13152235

Characterization of Chiral Nanostructured Surfaces Made via Colloidal Lithography

2023· article· en· W4385484236 on OpenAlexfundno aff
Sabine Portal, Carles Corbella, Oriol Arteaga, Alexander Martin, Trinanjana Mandal, Bart Kahr

Bibliographic record

VenueNanomaterials · 2023
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsnot available
FundersDivision of Materials ResearchYork UniversityUniversitat de BarcelonaNational Science Foundation
KeywordsCharacterization (materials science)NanotechnologyMaterials scienceLithographyColloidColloidal crystalColloidal particleChemical engineeringOptoelectronicsEngineering

Abstract

fetched live from OpenAlex

Optically anisotropic materials were produced via colloidal lithography and characterized using scanning electronic microscopy (SEM), confocal microscopy, and polarimetry. A compact hexagonal array mask composed of silica sub-micron particles was fabricated via the Langmuir-Blodgett self-assembly technique. Subsequently, the mask pattern was transferred onto monocrystalline silicon and commercial glass substrates using ion beam etching in a vacuum. Varying the azimuthal angle while etching at oblique incidence carved screw-like shaped pillars into the substrates, resulting in heterochiral structures depending on the azimuthal angle direction. To enhance the material's optical properties through plasmon resonance, gold films were deposited onto the pillars. Polarimetric measurements were realized at normal and oblique incidences, showing that the etching directions have a clear influence on the value of the linear birefringence and linear dichroism. The polarimetric properties, especially the chiroptical responses, increased with the increase in the angle of incidence.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.277
Teacher spread0.261 · 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.

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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueNanomaterialsSame topicLiquid Crystal Research AdvancementsFrench-language works237,207