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Record W2996283468 · doi:10.1002/adfm.201908218

Directed Emission from Self‐Assembled Microhelices

2019· article· en· W2996283468 on OpenAlexfundno aff
Lukas Helmbrecht, Mélissa Tan, Ruslan Röhrich, Marloes H. Bistervels, Bruno Ortiz Kessels, A. Femius Koenderink, Bart Kahr, Willem L. Noorduin

Bibliographic record

VenueAdvanced Functional Materials · 2019
Typearticle
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsnot available
FundersNederlandse Organisatie voor Wetenschappelijk OnderzoekDivision of Materials ResearchMaterials Research Science and Engineering Center, Harvard UniversityYork University
KeywordsMaterials scienceCrystalliteNanoscopic scaleFluorescenceHelix (gastropod)Polarization (electrochemistry)OpticsNanotechnologyOptoelectronicsChemistry

Abstract

fetched live from OpenAlex

Abstract Bottom‐up assembly can organize simple building blocks into complex architectures for light manipulation. The optical properties of self‐assembled polycrystalline barium carbonate/silica double helices are studied using fluorescent Fourier and Mueller matrix microscopy. Helices doped with fluorescein direct light emission along the long axis of the structure. Furthermore, light transmission measured normal and parallel to the long axis exhibits twist sense‐specific circular retardance and waveguiding, respectively, although the measurements suffer from depolarization. The helices thus integrate highly directional emission with enantiomorph‐specific polarization. This optical response emerges from the arrangement of nanoscopic mineral crystallites in the microscopic helix, and demonstrates how bottom‐up assembly can achieve ordering across multiple length scales to form complex functional materials.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0220.010

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 head0.225
Teacher spread0.219 · 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; both teacher heads agree on what is shown here.

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

Citations16
Published2019
Admission routes1
Has abstractyes

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