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Record W2743589446 · doi:10.1002/sia.6284

Insight into diacetylene photopolymerization in Langmuir‐Blodgett films using simultaneous AFM and fluorescence microscopy imaging

2017· article· en· W2743589446 on OpenAlexafffund
Hessamaddin Younesi Araghi, Matthew F. Paige

Bibliographic record

VenueSurface and Interface Analysis · 2017
Typearticle
Languageen
FieldChemistry
TopicPolydiacetylene-based materials and applications
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationUniversity of Saskatchewan
KeywordsDiacetylenePhotopolymerMonolayerFluorescenceMicroscopeFluorescence microscopePolymerMicroscopyPhase (matter)Langmuir–Blodgett filmChemistryAnalytical Chemistry (journal)Materials scienceOptical microscopeNanotechnologyScanning electron microscopeOpticsOrganic chemistryPolymerizationComposite material

Abstract

fetched live from OpenAlex

A phase‐separated monolayer film comprised of a mixture of 10, 12‐pentacosadiynoic acid (PCDA) with perfluorotetradecanoic acid (PF; CF 3 (CF 2 ) 12 COOH) has been characterized using a microscope that is capable of simultaneous atomic force microscope (AFM) imaging and fluorescence imaging. Design criteria for this instrument are described, as well as its application to investigating the mixed film systems. The product of PCDA photopolymerization has two phases, a red phase with strong fluorescence and a blue phase with no fluorescence. With the help of the dual AFM‐fluorescence microscope, it was found that both the red and the blue phase polymers were produced in the same sample from photoillumination, and the relative quantities of the different phases were quantified. Further, the importance of intrinsic mechanical stress in the films is discussed in terms of its influence on selectivity towards the red polymer phase.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 integrity0.0000.000
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 head0.009
GPT teacher head0.286
Teacher spread0.277 · 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
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

Citations8
Published2017
Admission routes2
Has abstractyes

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