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Record W4252333872 · doi:10.15680/ijirset.2015.0407201

Effects of Coating and Stirring on Superparamagnetic Iron Oxide Nanoparticles Size and Magnetic Characteristics

2015· article· en· W4252333872 on OpenAlex
Mohammad E. Khosroshahi Lida Ghazanfari

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Innovative Research in Science Engineering and Technology · 2015
Typearticle
Languageen
FieldEngineering
TopicCharacterization and Applications of Magnetic Nanoparticles
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSuperparamagnetismCoatingNanoparticleMaterials scienceMagnetic nanoparticlesIron oxideChemical engineeringOxideIron oxide nanoparticlesNanotechnologyMetallurgyMagnetizationMagnetic fieldPhysicsEngineering

Abstract

fetched live from OpenAlex

Considering the importance of nanoparticles physico-chemical properties in biomedical applications, we intend to describe and compares the results of fiveexperimental studies including: uncoated magnetic nanoparticles (MNPs), MNP + polyvinyl alcohol (PVA), MNP + amorphous silica (SiO 2 ) + gold (Au), and MNP + Au only. Controlled co-precipitation technique under N 2 gas is used to prevent undesirable critical oxidation of Fe 2+ .For uncoated Fe 3 O 4 NPs with saturation magnetization (M s ) range of (40-100) emu/g, smaller particles are synthesized by decreasing the NaOH concentration and increasing the stirring speed with the smallest value corresponding to 7.5 nm using 0.9 M of NaOH at 1500 rpm. The coatingprocess is done in four separate steps as follows:(i) the stable magnetic fluid containing well-dispersed Fe 3 O 4 /PVA nanocomposites which indicates a fast magnetic response with the smallest value of 7.5 nm using 0.9 M of NaOH at 750 rpm and M s of 50 emu/g, (ii) the synthesized Fe 3 O 4 NPs are stabilized using trisodium citrate (TSC) coating and then covered by SiO 2 layer using Stober method with the smallest value of 50 nm using 0.9 M of NaOH at 750 rpm and M s of 30 emu/g, (iii) small gold colloids (1-3 nm) are synthesized using Duff method and covered the amino functionalized particle surface of Fe 3 O 4 /SiO 2 nanoshells with the smallest value of 85 nm using 0.9 M of NaOH at 750 rpm and M s of 1.3 emu/g, (iv) also, bare superparamagneticIron oxide NPs (SPIONs) are covered by a thin layer of gold alone with the smallest value of 16 nm using 0.9 M of NaOH at 1500 rpm and M s of 12 emu/g. Magnetic properties and size of nanoshells are assessed using vibrating sample magnetometer (VSM)and transmission electron microscope (TEM). Furthermore, M s of 7.5 nm magnetite is high enough to be used as contrast agent for photoacoustic (PAI) and magnetic resonance imaging (MRI).

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.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.195
Threshold uncertainty score0.277

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.302
Teacher spread0.284 · 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