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Record W4409172787 · doi:10.3390/ma18071658

Synthesis, Characterization, and Investigation of the Properties of a New Promising Poly(Azomethine) Organic Semiconductor Material

2025· article· en· W4409172787 on OpenAlexaff
Jihane Ismaili, Chouki Zerrouki, Najla Fourati, Stéphanie Leroy‐Lhez, Daniel Montplaisir, Nicolas Villandier, Rachida Zerrouki

Bibliographic record

VenueMaterials · 2025
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsThermogravimetric analysisMaterials sciencePolymerDifferential scanning calorimetryGel permeation chromatographyGlass transitionSolubilityPolymer chemistryChemical engineeringCondensation polymerThermal decompositionPhysical chemistryOrganic chemistryComposite materialChemistry

Abstract

fetched live from OpenAlex

A new poly(azomethine) with improved solubility was successfully prepared by the polycondensation of terephthalaldehyde and 2,2-Bis[4-(4-aminophenoxy)phenyl]-hexafluoropropane (4-BDAF) under green chemistry conditions. This new polymer containing hexafluoroisopropylidene was compared with a polymer containing isopropylidenediphenyl to study the influence of the presence of fluorine atoms on the properties of the polymer. Both were characterized by nuclear magnetic resonance (NMR), their molecular weight was measured by gel permeation chromatography (GPC), and their morphology was studied by X-ray diffraction (XRD). The two polymers obtained were soluble in most polar aprotic solvents and even in less polar solvents, which are practical and easily accessible solvents. Their thermal properties were determined by a thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). These two new polymers showed high resistance to thermal decomposition up to 490 °C, with a glass transition temperature (Tg) of 180 °C. The photophysical properties were studied by UV/Visible absorption. The polymers were doped and then deposited on cellulose filaments, an approach that made it possible to produce self-supporting conductive composites thanks to their mechanical properties. The topography of the resulting materials was characterized at submicron scales before estimating their electronic conductivity and gap energy by diffuse reflection spectroscopy.

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 score0.408

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 head0.026
GPT teacher head0.231
Teacher spread0.205 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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