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Record W3093033104 · doi:10.1016/j.arabjc.2020.10.014

Progress on phthalocyanine-conjugated Ag and Au nanoparticles: Synthesis, characterization, and photo-physicochemical properties

2020· article· en· W3093033104 on OpenAlexaff
Shereen A. Majeed, Kutloano Edward Sekhosana, Ahmad Tuhl

Bibliographic record

VenueArabian Journal of Chemistry · 2020
Typearticle
Languageen
FieldMaterials Science
TopicPorphyrin and Phthalocyanine Chemistry
Canadian institutionsAcadia University
Fundersnot available
KeywordsChemistryPhthalocyanineNanomaterialsSinglet oxygenNanoparticleSpectroscopyX-ray photoelectron spectroscopyDynamic light scatteringTransmission electron microscopyConjugated systemInfrared spectroscopyFourier transform infrared spectroscopyFluorescence spectroscopyPhotochemistryFluorescenceNanotechnologyChemical engineeringOrganic chemistryPolymerMaterials scienceOxygen

Abstract

fetched live from OpenAlex

Phthalocyanine (Pc) complexes are an important class of dyes with numerous (e.g., biological, photophysical, and analytical) applications. Among the methods used to improve the properties of these complexes, one should mention the introduction of different substituents, variation of the central metal ion, ligand exchange, and conjugation to nanomaterials (e.g., carbon-based nanomaterials and metal nanoparticles (NPs)). This work briefly reviews Pc complex conjugation to Ag and Au NPs, highlights the different NP shapes, and discusses the diversity of conjugation approaches. Moreover, the use of UV–Vis spectroscopy, powder X-ray diffraction, X-ray photoelectron spectroscopy, transmission electron microscopy, atomic force microscopy, dynamic light scattering and Fourier transform infrared spectroscopy to characterize Pc-NP hybrids is summarized. The effect of conjugation on Pc photo-physicochemical properties (fluorescence, singlet oxygen generation, triplet state formation, and optical limiting behavior) is discussed, and future perspectives for the synthesis and applications of new hybrids are provided.

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 score0.002
Threshold uncertainty score0.704

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 head0.019
GPT teacher head0.217
Teacher spread0.199 · 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

Citations22
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueArabian Journal of ChemistrySame topicPorphyrin and Phthalocyanine ChemistryFrench-language works237,207