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Record W2581073640 · doi:10.1021/acs.macromol.6b02499

Polymer Assemblies with Nanostructure-Correlated Aggregation-Induced Emission

2017· article· en· W2581073640 on OpenAlex

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.

Bibliographic record

VenueMacromolecules · 2017
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsUniversity of Waterloo
FundersNational Natural Science Foundation of China
KeywordsMicelleNanostructurePolymerCopolymerPolymerizationVesicleMethacrylateChemical engineeringFluorescenceMaterials scienceSelf-assemblyPolymer chemistryChemistryMonomerNanotechnologyOrganic chemistryAqueous solutionMembrane

Abstract

fetched live from OpenAlex

The correlation of aggregation-induced emission (AIE) to the nanostructure of polymer assemblies was investigated. A series of AIE-active PDMA- b -P(BzMA-TPE) [PDMA: poly( N, N -dimethylaminoethyl methacrylate); P(BzMA-TPE): poly[benzyl methacrylate- co -1-ethenyl-4-(1,2,2-triphenylethenyl)benzene]] assemblies with controlled nanostructures were prepared via polymerization-induced self-assembly of BzMA and TPE, an AIEgen, in the presence of PDMA macro-chain-transfer agents. We found that the fluorescence intensity and fluorescent quantum yield increase in the order of vesicles > wormlike micelles > spherical micelles. For spherical micelles and vesicles, the AIE effect strengthens with increase in micellar size and wall thickness, respectively. As the AIE effect indicates the packing compactness of the AIEgens, the discovered structure-correlated emission can be attributed to the stress variation of polymer chains in the aggregates. AIE is therefore potentially useful as a probe for the investigation and understanding of nanostructure and evolution process of polymer self-assemblies.

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 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 score0.005
Threshold uncertainty score0.698

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 studies0.0010.000
Scholarly communication0.0010.000
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 head0.013
GPT teacher head0.251
Teacher spread0.238 · 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