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Record W2530619979 · doi:10.1002/anie.201607406

Nanofibrillar Stimulus‐Responsive Cholesteric Microgels with Catalytic Properties

2016· article· en· W2530619979 on OpenAlexafffund
Sangho Cho, Yunfeng Li, Minseok Seo, Eugenia Kumacheva

Bibliographic record

VenueAngewandte Chemie International Edition · 2016
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials sciencePolymerSupramolecular chemistryNanoparticleCatalysisChemical engineeringNanotechnologyCelluloseNanocrystalComposite numberChemistryMoleculeOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

We report composite stimulus-responsive cholesteric catalytically active microgels derived from filamentous supramolecular building blocks: cellulose nanocrystals (CNCs). The variation in the microgel dimensions and pitch in response to the change in ambient conditions was governed by the polymer component. The cholesteric morphology of the microgels resulted from the self-organization of CNCs in spherical confinement. The microgels exhibited excellent structural integrity and functioned as microreactors in catalytic hydrolysis reactions and in the synthesis of metal nanoparticles. Because of these collective properties, the reported microgels show much promise for application in the design of functional responsive 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)0.000
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 score0.015
Threshold uncertainty score0.645

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)0.0000.001

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 head0.021
GPT teacher head0.264
Teacher spread0.243 · 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

Citations41
Published2016
Admission routes2
Has abstractyes

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