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Record W2794225345 · doi:10.1002/slct.201702698

Effect of Coral‐Shaped Yttrium Iron Garnet Particles on the EMI Shielding Behaviour of Yttrium Iron Garnet‐Polyaniline‐Wax Composites

2018· article· en· W2794225345 on OpenAlexaff
Harish Kumar Choudhary, Rajeev Kumar, Shital Patangrao Pawar, A.V. Anupama, Suryasarathi Bose, Balaram Sahoo

Bibliographic record

VenueChemistrySelect · 2018
Typearticle
Languageen
FieldMaterials Science
TopicElectromagnetic wave absorption materials
Canadian institutionsUniversity of Calgary
FundersDepartment of Science and Technology, Government of Kerala
KeywordsMaterials scienceElectromagnetic shieldingYttrium iron garnetComposite materialWaxPolyanilineMicrowaveDielectricYttriumEMIElectromagnetic interferenceMetallurgyCondensed matter physicsOptoelectronicsElectrical engineeringPolymer

Abstract

fetched live from OpenAlex

Abstract We report the physicochemical insight into the role of coral‐shaped yttrium‐iron‐garnet (YIG) particles for high electromagnetic interference (EMI) shielding behaviour of YIG‐polyaniline (PANI)‐Wax composites. We studied the total shielding effectiveness (SE T ) of various compositions of the composites in X and K u ‐band frequencies (8‐18 GHz) and came upon with a critical concentration (20 wt% of YIG) for which SE T is maximum (‐44.8 dB). At this critical concentration, the coral shape of YIG helps in effectively increasing the YIG‐PANI interfaces necessary for the multiple scattering of electromagnetic (EM) waves. The scattered microwave is then trapped within the dense coral‐network of YIG until they are absorbed therein by PANI via conduction loss; thereby, dramatically enhancing the microwave attenuation. The detailed EMI shielding mechanism is explained based on electrical and magnetic properties of the composites. Our result demonstrates the importance of morphology of the dielectric/magnetic particles and their concentration in the composites for designing an efficient EMI shield.

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.257
Teacher spread0.246 · 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

Citations67
Published2018
Admission routes1
Has abstractyes

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