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Record W2512806667 · doi:10.1002/anie.201606283

Polymer and Mesoporous Silica Microspheres with Chiral Nematic Order from Cellulose Nanocrystals

2016· article· en· W2512806667 on OpenAlex
Pei‐Xi Wang, Wadood Y. Hamad, Mark J. MacLachlan

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAngewandte Chemie International Edition · 2016
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsFPInnovationsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaFPInnovations
KeywordsMaterials scienceLiquid crystalPolymerChemical engineeringMesoporous materialPolymerizationEmulsionNanocrystalNanotechnologyComposite materialOrganic chemistryOptoelectronicsChemistryCatalysis

Abstract

fetched live from OpenAlex

Polymer microspheres with chiral nematic order were obtained from an emulsion polymerization technique using cellulose nanocrystals (CNCs) as the template. The growth of the liquid crystals from tiny tactoids to droplets with spherical symmetry was captured and investigated by both optical and electron microscopy for the first time. The size of the microspheres could be tuned between tens and hundreds of micrometers; to obtain single, integrated chiral nematic kernels, the size of water droplets in the emulsion should be similar to that of CNC tactoids. Through a double-matrix templating method, novel silica microspheres with chiral nematic order were fabricated, which showed a high surface area and mesoporosity. The methods developed here may help to reveal the evolution of other self-assembling systems, and these materials have potential applications in optical devices and chiral separations.

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 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 score0.005
Threshold uncertainty score0.996

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.011
GPT teacher head0.257
Teacher spread0.246 · 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