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Record W2332628846 · doi:10.1021/acs.langmuir.5b00728

Coassembly of Gold Nanoparticles and Cellulose Nanocrystals in Composite Films

2015· article· en· W2332628846 on OpenAlexafffund
Ariella Lukach, Héloïse Thérien‐Aubin, Ana Querejeta‐Fernández, Natalie Pitch, Grégory Chauve, Myriam Méthot, Jean Bouchard, Eugenia Kumacheva

Bibliographic record

VenueLangmuir · 2015
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsFPInnovationsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceComposite numberNanocrystalNanoparticleColloidal goldNanocompositeCelluloseNanotechnologyFabricationChemical engineeringComposite material

Abstract

fetched live from OpenAlex

Coassembly of nanoparticles with different size-, shape-, and composition-dependent properties is a promising approach to the design and fabrication of functional materials and devices. This paper reports the results of a detailed investigation of the formation and properties of free-stranding composite films formed by the coassembly of cellulose nanocrystals and shape-isotropic plasmonic gold nanoparticles. The effect of gold nanoparticle size, surface charge, and concentration on the structural and optical properties of the composite films has been studied. The composite films retained photonic crystal and chiroptical activity properties. The size and surface charge of gold nanoparticles had a minor effect on the structure and properties of the composite films, while the concentration of gold nanoparticles in the composite material played a more significant role and can be used to fine-tune the optical properties of materials derived from cellulose nanocrystals. These findings significantly broaden the range of nanoparticles that can be used for producing nanocomposite materials based on cellulose nanocrystals. The simplicity of film preparation, the abundance of cellulose nanocrystals, and the robust, free-standing nature of the composite films offer highly advantageous features and pave the way for the generation of functional materials with coupled optical properties.

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 score0.002
Threshold uncertainty score0.313

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 head0.036
GPT teacher head0.296
Teacher spread0.260 · 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

Citations68
Published2015
Admission routes2
Has abstractyes

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