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Record W2056630079 · doi:10.5539/apr.v5n1p19

The Effect of Gelation on the Apparent Magnetism of ZnFe2O4 Sol-Gel Systems

2013· article· en· W2056630079 on OpenAlexvenueno aff
Yueqiang Lin, Jian Li, Xiaodong Liu, Jun Fu, Lihua Lin, Longlong Chen

Bibliographic record

VenueApplied Physics Research · 2013
Typearticle
Languageen
FieldEngineering
TopicCharacterization and Applications of Magnetic Nanoparticles
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMagnetismMagnetizationThixotropyMaterials scienceDecoupling (probability)ColloidFerrofluidCondensed matter physicsDegrees of freedom (physics and chemistry)Brownian motionSPHERESChemical physicsPhysicsThermodynamicsMagnetic fieldChemistryComposite materialPhysical chemistryQuantum mechanics

Abstract

fetched live from OpenAlex

Experiments have shown that for thixotropic sol-gel systems consisting of ZnFe2O4 nanoparticles without any matrix material, the measured magnetization, or susceptibility of gels, are greater than those of sols. For the reduced susceptibility, a system with a volume fraction of particles of fv=2.0% is lower than a system with fv=1.5%. These results have been interpreted in terms of a magnetization mechanism based on the Brownian rotation of the moments fixed inside the colloidal particles, which would be dramatically affected by the non-magnetic hydrodynamic interaction. For weakly cross-linked gels, the translational degree of freedom is “frozen” while the rotational degree of freedom remains unchanged, so that their hydrodynamic interaction effect is weaker, and they are more easily magnetized than the sols with both rotational and translational degrees of freedom. The action of gelation preventing the hydrodynamic interaction effect on the magnetization process can be referred to as the “gelation decoupling”. Correspondingly, such behavior of the hydrodynamic interaction in affecting the apparent magnetism can be referred to as a “viscomagnetic effect”.

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)0.001
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 score0.130
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.024
GPT teacher head0.269
Teacher spread0.245 · 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
Published2013
Admission routes1
Has abstractyes

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