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Record W2398229532

SYNTHESIS AND CHARACTERIZATION OF POLYSTYRENE COATED FUNCTIONALIZED γ -Fe2O3 NANOPARTICLES

2014· article· en· W2398229532 on OpenAlexvenueno aff
Tayyab Ali, A. Venkataraman

Bibliographic record

VenueInternational Journal of Chemistry · 2014
Typearticle
Languageen
FieldEnergy
TopicIron oxide chemistry and applications
Canadian institutionsnot available
Fundersnot available
KeywordsPolystyreneNanoparticlePolymerTransmission electron microscopyCharacterization (materials science)NanotechnologyChemistryChemical engineeringScanning electron microscopeDrug deliveryPolymer chemistryMaterials scienceOrganic chemistry
DOInot available

Abstract

fetched live from OpenAlex

γ-Fe2O3 nanoparticles showing supermagnetic behaviour have been widely studied in recent years for various applications. Polymer coated functionalized γ-Fe2O3 nanoparticles have wide applications which attracted many researchers to study their different nature when they are supported with polymers. Functionalized γ-Fe2O3 nanoparticles has many applications in medical field such as MRI contrast, drug delivery, hyperthermia, magnetic gels, in cancer treatment and also used in memory devices, supermagnetic materials etc. In the present study we synthesized the polystyrene coated functionalized γ-Fe2O3 nanoparticles (PSCFNPs) in the weight ratio through grafting onto method. These nanoparticles were characterized and studied its magnetic property employing B-H loop tracer, molecular structure through FT-IR spectroscopy, thermal study employing TGA, DSC and morphology through Scanning Electron Microscopy (SEM) & transmission electron microscopy (TEM) techniques. Through the mentioned characterization techniques we obtained the formation of fine polystyrene coated functionalized γ-Fe2O3 nanoparticles. The medical applications of the nanoparticles with tailored surfaces by biocompatible polymers are envisioned.

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 score0.009
Threshold uncertainty score0.748

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)0.0010.000

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 head0.008
GPT teacher head0.224
Teacher spread0.217 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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Same venueInternational Journal of ChemistrySame topicIron oxide chemistry and applicationsFrench-language works237,207