Publication:
Giant magnetoimpedance effect: Concept and prediction in amorphous materials

dc.contributor.buuauthorDerebaşı, Naim
dc.contributor.departmentFen Edebiyat Fakültesi
dc.contributor.departmentFizik Bölümü
dc.contributor.orcid0000-0003-2546-0022
dc.contributor.researcheridAAI-2254-2021
dc.contributor.scopusid11540936300
dc.date.accessioned2023-05-10T13:33:14Z
dc.date.available2023-05-10T13:33:14Z
dc.date.issued2013-03
dc.description.abstractGiant magneto impedance (GMI) effect was experimentally measured on as-cast, post-production and coated with chemical technique amorphous wire and ribbon materials consisted of varied chemical composition over a frequency range from 0.1 to 8 MHz under a static magnetic field between -8 and +8 kA/m. The results show that each amorphous sample has a certain operational frequency for which the GMI effect has maximum magnitude and the other parameters such as annealing and coating have a significant influence on the GMI effect. It is believed that the domain structure and wall mechanism in the material are responsible for this behaviour. A 3-node input layer, 1-node output layer artificial neural network (ANN) model with three hidden layers including 30 neurons and full connectivity between the nodes was developed. A total of 1600 input vectors obtained from varied treated samples was available in the training data set. After the network was trained, better results were obtained from the network formed by the hyperbolic tangent transfer function in the hidden layers, there was a sigmoid transfer function in the output layer and we predicted the GMI. Comparing the predicted values obtained from the ANN model with the experimental data indicates that a well-trained neural network model provides very accurate results.
dc.identifier.citationDerebaşı, N. (2013). “Giant magnetoimpedance effect: Concept and prediction in amorphous materials”. Journal of Superconductivity and Novel Magnetism, 26(4), Special Issue, 1075-1078.
dc.identifier.endpage1078
dc.identifier.issn1557-1939
dc.identifier.issn1557-1947
dc.identifier.issue4, Special Issue
dc.identifier.scopus2-s2.0-84876471638
dc.identifier.startpage1075
dc.identifier.urihttps://doi.org/10.1007/s10948-012-1923-4
dc.identifier.urihttp://hdl.handle.net/11452/32614
dc.identifier.volume26
dc.identifier.wos000317014500062
dc.indexed.wosSCIE
dc.indexed.wosCPCIS
dc.language.isoen
dc.publisherSpringer
dc.relation.bap2009/29
dc.relation.journalJournal of Superconductivity and Novel Magnetism
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectPhysics
dc.subjectGMI effect
dc.subjectAmorphous materials
dc.subjectDomains
dc.subjectArtificial neural network
dc.subjectRibbons
dc.subjectWires
dc.subjectCoated materials
dc.subjectMagnetic domains
dc.subjectNeural networks
dc.subjectTransfer functions
dc.subjectArtificial neural network models
dc.subjectChemical compositions
dc.subjectGiant magneto impedance effect
dc.subjectGMI effects
dc.subjectNeural network model
dc.subjectOperational frequency
dc.subjectSigmoid transfer function
dc.subjectStatic magnetic fields
dc.subjectAmorphous materials
dc.subject.scopusMagnetic Sensors; Electric Impedance; Ribbons
dc.subject.wosPhysics, applied
dc.subject.wosPhysics, condensed matter
dc.titleGiant magnetoimpedance effect: Concept and prediction in amorphous materials
dc.typeArticle
dc.typeProceedings Paper
dc.wos.quartileQ3 (Physics, applied)
dc.wos.quartileQ4 (Physics, condensed matter)
dspace.entity.typePublication
local.contributor.departmentFen Edebiyat Fakültesi/Fizik Bölümü
local.indexed.atScopus
local.indexed.atWOS

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