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Record W2050488973 · doi:10.1063/1.1829771

Response of magnetic nanoparticles to microwaves

2004· article· en· W2050488973 on OpenAlexaff
D. Walton, Harald N. Boehnel, David J. Dunlop

Bibliographic record

VenueApplied Physics Letters · 2004
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Synthesis of Ferrites
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsMagnonCondensed matter physicsMicrowaveMagnetiteAbsorption (acoustics)Ferromagnetic resonanceFerromagnetismMaterials scienceRelaxation (psychology)NanoparticleMagnetic nanoparticlesPhoton energyMagnetic fieldPhotonMagnetizationOpticsNanotechnologyPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

Two important processes in ferromagnetic resonance are the first-order absorption of a photon and creation of a single magnon, and a second-order process in which the absorption of a photon results in the creation of two magnons of equal and opposite wave vector [M. Sparks, Ferromagnetic Relaxation (McGraw–Hill, New York, 1964)]. We have found that under resonance conditions for the second-order process, samples containing ∼0.1% magnetite absorb energy from the microwave field at the same rate as a solid magnetite sample. The resultant very high-energy density in the magnetic nanoparticles, coupled with a significant thermal energy barrier with the matrix, leads to a large temperature difference between the grains and their surroundings that makes it possible to magnetize and demagnetize the sample with a relatively small increase in sample temperature.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.012
GPT teacher head0.204
Teacher spread0.192 · 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 source (direct Gemma or distilled Codex), 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

Citations23
Published2004
Admission routes1
Has abstractyes

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Same venueApplied Physics LettersSame topicMagnetic Properties and Synthesis of FerritesFrench-language works237,207