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Record W2550212253 · doi:10.1002/marc.201600568

Synthesis of Site‐Specific Dye‐Labeled Polymer via Atom Transfer Radical Polymerization (ATRP) for Quantitative Characterization of the Well‐Defined Interchain Distance

2016· article· en· W2550212253 on OpenAlexaff
Ye Sha, Dongliang Qi, Shaochuan Luo, Xinghua Sun, Xiaoliang Wang, Gi Xue, Dongshan Zhou

Bibliographic record

VenueMacromolecular Rapid Communications · 2016
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsMinistry of Education and Child Care
FundersNational Natural Science Foundation of China
KeywordsFörster resonance energy transferAtom-transfer radical-polymerizationFluorophorePolymerPolymerizationMonomerMoietyFluorescenceRadical polymerizationPolymer chemistryPhotochemistryMethyl methacrylateMaterials sciencePhotopolymerChemistryStyreneCopolymerOrganic chemistry

Abstract

fetched live from OpenAlex

Novel difunctional initiators that incorporate Förster/fluorescence resonance energy transfer (FRET) pairs are generated to carry out atom transfer radical polymerization of styrene, methyl methacrylate, and n-butyl methacrylate monomers by an efficient manner. Based on the chemical structures of the initiators, the locations of the fluorophore moiety are dictated to be in the center of the chain with accurately quantified chain functionality (>90% labeling ratio). The site-specific integration of FRET dyes into separate polymer chain centers allows for characterization of the well-defined interchain distance quantitatively based on the response between these fluorescent probes. The reliability of this technique is verified in bulk state, which is in well agreement with the theoretical ones. This well-defined FRET system is expected to be a promising candidate to provide a distinct physical image at a microscopic level regarding scaling chain dimension, chain interpenetration, and polymer compatibility.

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: none
Teacher disagreement score0.789
Threshold uncertainty score0.519

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 science0.0010.000
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 head0.015
GPT teacher head0.234
Teacher spread0.219 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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