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Record W1548617052 · doi:10.1063/1.1512693

Magnetic force microscopy of ferromagnetic nanoparticles formed in Al2O3 and SiO2 by ion implantation

2002· article· en· W1548617052 on OpenAlexaff
C. E. Vallet, C. W. White, S. P. Withrow, J. D. Budai, L. A. Boatner, K. D. Sorge, J. R. Thompson, K. S. Beaty, A. Meldrum

Bibliographic record

VenueJournal of Applied Physics · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMagnetic force microscopeTransmission electron microscopyFerromagnetismMagnetismMaterials scienceMagnetic nanoparticlesNanoparticleIon implantationMicroscopyIonNanotechnologyAnalytical Chemistry (journal)ChemistryMagnetic fieldMagnetizationCondensed matter physicsOpticsPhysics

Abstract

fetched live from OpenAlex

Magnetic force microscopy (MFM) has been used to investigate the properties of ferromagnetic FePt nanoparticles produced by the implantation of Fe and Pt ions into single-crystal Al2O3 or fused SiO2 followed by thermal processing. The MFM results are compared to cross-section and plan view transmission electron microscopy images of the same samples. We demonstrate that MFM can detect magnetism in nanosized particles that are situated several hundred nm below the sample surface. MFM is shown to be a promising tool for studying the characteristics of magnetic nanoparticles produced by ion implantation.

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 score0.024
Threshold uncertainty score0.427

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 head0.007
GPT teacher head0.242
Teacher spread0.235 · 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

Citations22
Published2002
Admission routes1
Has abstractyes

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