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Record W7117416123 · doi:10.53063/synsint.2025.54306

A high-impact review on M-type hexaferrites: Structural, magnetic and microwave absorption characteristics with emerging trends

2025· article· W7117416123 on OpenAlexvenueno aff
Seyed Salman Seyed Afghahi, Reza Torkamani, P. Dehghani

Bibliographic record

VenueSynthesis and Sintering · 2025
Typearticle
Language
FieldMaterials Science
TopicElectromagnetic wave absorption materials
Canadian institutionsnot available
Fundersnot available
KeywordsMicrowaveAttenuationAbsorption (acoustics)DielectricDielectric lossElectromagnetic radiationAbsorption efficiency

Abstract

fetched live from OpenAlex

The use of absorbers is critical for protecting human health, enabling stealth applications, and preventing electromagnetic interference. Although various absorbers have been developed in recent years, many suffer from poor synergy and low attenuation efficiency, resulting in limited performance. Also, the factors affecting the increase in the effective absorption bandwidth have not been well addressed. Hexaferrites, with their ability to provide magnetic loss along with dielectric loss, are promising candidates for microwave absorbers. However, hexaferrites currently lack the necessary efficiency, and their microwave attenuation properties need to be enhanced. In this review article, we examine recent studies on M-type hexaferrites, focusing on the parameters influencing microwave absorption properties. The magnetic properties of these materials, along with the origins of their magnetic behavior, the structural characteristics, and various synthesis methods of hexaferrites, are thoroughly analyzed due to their significant impact on absorption performance. Finally, in this review article, we present suggestions that can lead to improved efficiency and use of hexaferrites in industry as adsorbents.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.294
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.267
Teacher spread0.256 · 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.

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

Citations5
Published2025
Admission routes1
Has abstractyes

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