MétaCan
Menu
Back to cohort
Record W2073850847 · doi:10.1155/2008/609184

A Simple Method for Forming Hybrid Core‐Shell Nanoparticles Suspended in Water

2008· article· en· W2073850847 on OpenAlexaff
Jean‐Christophe Daigle, Jérôme P. Claverie

Bibliographic record

VenueJournal of Nanomaterials · 2008
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsMaterials scienceNanoparticleChemical engineeringChain transferDispersantPolymerizationHybrid materialAcrylateNanocompositePolymerButyl acrylateMonomerAcrylic acidEmulsion polymerizationRadical polymerizationDispersion (optics)NanotechnologyComposite material

Abstract

fetched live from OpenAlex

Core‐shell hybrid nanoparticles, where the core is an inorganic nanoparticle and the shell an organic polymer, are prepared by a two‐step method. Inorganic nanoparticles are first dispersed in water using poly(acrylic acid) (PAA) prepared by reversible addition fragmentation chain transfer (RAFT) polymerization as dispersant. Then, the resulting dispersion is engaged in a radical emulsion polymerization process whereby a hydrophobic organic monomer (styrene and butyl acrylate) is polymerized to form the shell of the hybrid nanoparticle. This method is extremely versatile, allowing the preparation of a variety of nanocomposites with metal oxides (alumina, rutile, anatase, barium titanate, zirconia, copper oxide), metals (Mo, Zn), and even inorganic nitrides (Si3N4).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.035
GPT teacher head0.295
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations58
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of NanomaterialsSame topicAdvanced Polymer Synthesis and CharacterizationFrench-language works237,207