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Record W2243707952 · doi:10.1139/cjp-2013-0486

Enhancement of optical properties of poly (9,9′-di-n-octylfluorenyl-2,7-diyl) in conjugated polymer/TiO<sub>2</sub> nanocomposites

2013· article· en· W2243707952 on OpenAlexvenueno aff
Bandar Ali Al‐Asbahi, Mohammad Hafizuddin Hj Jumali

Bibliographic record

VenueCanadian Journal of Physics · 2013
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsnot available
Fundersnot available
KeywordsNanocompositeConjugated systemPolymerMonomerSpectral linePhysicsColloidAbsorption (acoustics)Materials scienceAnalytical Chemistry (journal)Chemical engineeringNanotechnologyOpticsNuclear magnetic resonanceOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

The influence of colloidal TiO 2 nanoparticle contents on the optical properties of poly (9,9′-di-n-octylfluorenyl-2,7-diyl) conjugated polymer (PFO) has been investigated. The solution blending method was used to prepare homogenous PFO/TiO 2 nanocomposite. The nanocomposite films were prepared on glass substrates using the spin-coating technique. The films were divided into two groups, the first was left to dry at room temperature while the second was heat-treated at 120 °C for 1 h. Absorption and emission spectra showed that the PFO existed in α- and β-phases morphology having monomeric, excimeric, and double excimeric states. In addition, both spectra revealed that TiO 2 contents and heat treatment temperature extended the conjugation length of PFO. Finally, emission spectra for both cases exhibited decreasing in the line width of zero-phonon emission spectra and increasing in the vibronic splitting energy, upon increment of the TiO 2 , led to a significant increase in π-electron delocalization and lower degree in chain disorder.

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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.870

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 science0.0000.000
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 head0.018
GPT teacher head0.214
Teacher spread0.196 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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