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Record W2050488973 · doi:10.1063/1.1829771

Response of magnetic nanoparticles to microwaves

2004· article· en· W2050488973 on OpenAlex

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

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.

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 score0.008
Threshold uncertainty score0.443

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 head0.012
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