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Record W4366988527 · doi:10.3390/mi14050925

SiCNFe Ceramics as Soft Magnetic Material for MEMS Magnetic Devices: A Mössbauer Study

2023· article· en· W4366988527 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

VenueMicromachines · 2023
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced ceramic materials synthesis
Canadian institutionsConcordia University
Fundersnot available
KeywordsMaterials scienceCeramicParamagnetismMicrofabricationMicroelectromechanical systemsNanoparticleMagnetic nanoparticlesChemical engineeringMagnetFerromagnetismAnalytical Chemistry (journal)NanotechnologyComposite materialCondensed matter physicsChemistryMechanical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Polymer-derived SiCNFe ceramics is a prospective material that can be used as soft magnets in MEMS magnetic applications. The optimal synthesis process and low-cost appropriate microfabrication should be developed for best result. Homogeneous and uniform magnetic material is required for developing such MEMS devices. Therefore, the knowledge of exact composition of SiCNFe ceramics is very important for the microfabrication of magnetic MEMS devices. The Mössbauer spectrum of SiCN ceramics, doped with Fe (III) ions, and annealed at 1100 °C, was investigated at room temperature to accurately establish the phase composition of Fe-containing magnetic nanoparticles, which were formed in this material at pyrolysis and which determine their magnetic properties. The analysis of Mössbauer data shows the formation of several Fe-containing magnetic nanoparticles in SiCN/Fe ceramics, such as α-Fe, FexSiyCz, traces of Fe-N and paramagnetic Fe3+ with octahedral oxygen environment. The presence of iron nitride and paramagnetic Fe3+ ions shows that the pyrolysis process was not completed in SiCNFe ceramics annealed at 1100 °C. These new observations confirm the formation of different Fe-containing nanoparticles with complex composition in SiCNFe ceramic composite.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.014
GPT teacher head0.276
Teacher spread0.262 · 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