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Record W2096352244 · doi:10.1002/pola.26070

Synthesis of single‐core and multiple‐core core‐shell nanoparticles by RAFT emulsion polymerization: Lead sulfide‐copolymer nanocomposites

2012· article· en· W2096352244 on OpenAlexaff
Paramita Das, Jérôme P. Claverie

Bibliographic record

VenueJournal of Polymer Science Part A Polymer Chemistry · 2012
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsEmulsion polymerizationRaftChain transferPolymerizationCopolymerPolymer chemistryDispersion polymerizationMaterials scienceChemical engineeringNanoparticleReversible addition−fragmentation chain-transfer polymerizationAcrylateDispersityButyl acrylateRadical polymerizationPolymerNanotechnologyComposite material

Abstract

fetched live from OpenAlex

Abstract We report here a simple and direct route for the preparation of lead sulfide (PbS) quantum dots (QDs) embedded into polymeric nanospheres by emulsion polymerization. In this process, QDs are first dispersed in an aqueous solution containing a statistical oligomer constituted of five butyl acrylate and ten acrylic acid units prepared by reversible addition fragmentation chain transfer (RAFT) polymerization using a trithiocarbonate as RAFT agent. Then, the dispersion of PbS QDs is engaged into an emulsion polymerization process to form core‐shell nanoparticles. Transmission electron microscopy reveals the presence of single‐core core‐shell particles at low concentration of PbS QD, whereas multiple‐core core‐shell particles containing either well separated or aggregated PbS QDs are formed at high concentration of PbS QDs. © 2012 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2012

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)
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 score0.073
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.249
Teacher spread0.220 · 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.

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

Citations40
Published2012
Admission routes1
Has abstractyes

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