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Materials
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Modeling and Characterization of Magnetic Materials
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Modeling and Characterization of Magnetic Materials

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Materials Simulation and Design".

Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 3463

Special Issue Editors

Prof. Dr. Aphrodite Ktena

E-Mail Website
Guest Editor
Energy Systems Laboratory, General Department, National & Kapodistrian University of Athens, Euripus Campus, 34400 Evia, Greece
Interests: measurement systems and technology; modeling and optimization; RES microgrids; magnetism and magnetic materials; non destructive testing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Evangelos Hristoforou

E-Mail Website
Co-Guest Editor
School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece
Interests: sensors; magnetic materials; biotechnology; structure and properties of materials; steel health monitoring
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Alfredo Garcia–Arribas

E-Mail Website
Co-Guest Editor
Departamento de Electricidad y Electrónica, Universidad del País Vasco (UPV/EHU), 48080 Bilbao, Spain
Interests: magnetic materials for sensors and actuators and nano-bioapplications

Special Issue Information

Dear Colleagues,

Developments in materials science and engineering as well as in ICT tools and industrial applications present the magnetics community with new challenges in expanding the foundation of our knowledge on determining, controlling and tailoring magnetic properties, designing and characterizing new materials, developing new applications based on magnetic phenomena.

The goal of this Special Issue is to offer a comprehensive overview of the state of the art in the modeling and characterization of conventional and novel magnetic materials at various length and time scales, not limited but with special emphasis to applications.

We invite contributions that, among others, target the development and innovative uses of magnetic materials, the understanding of underlying physics and control of magnetic phenomenology by relating microstructure to magnetic macroscopic behavior, the improved process control utilizing or compensating for magnetic phenomena.

Prof. Aphrodite Ktena
Prof. Evangelos Hristoforou
Prof. Alfredo Garcia–Arribas
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Materials is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • hysteresis modeling
  • barkhausen noise
  • magnetoelasticity
  • multi-scale modeling
  • magnetization processes

Published Papers (1 paper)

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Research

14 pages, 4244 KiB  
Article
Dynamic Ferromagnetic Hysteresis Modelling Using a Preisach-Recurrent Neural Network Model
by Christian Grech, Marco Buzio, Mariano Pentella and Nicholas Sammut
Materials 2020, 13(11), 2561; https://doi.org/10.3390/ma13112561 - 04 Jun 2020
Cited by 21 | Viewed by 2959
Abstract
In this work, a Preisach-recurrent neural network model is proposed to predict the dynamic hysteresis in ARMCO pure iron, an important soft magnetic material in particle accelerator magnets. A recurrent neural network coupled with Preisach play operators is proposed, along with a novel [...] Read more.
In this work, a Preisach-recurrent neural network model is proposed to predict the dynamic hysteresis in ARMCO pure iron, an important soft magnetic material in particle accelerator magnets. A recurrent neural network coupled with Preisach play operators is proposed, along with a novel validation method for the identification of the model’s parameters. The proposed model is found to predict the magnetic flux density of ARMCO pure iron with a Normalised Root Mean Square Error (NRMSE) better than 0.7%, when trained with just six different hysteresis loops. The model is evaluated using ramp-rates not used in the training procedure, which shows the ability of the model to predict data which has not been measured. The results demonstrate that the Preisach model based on a recurrent neural network can accurately describe ferromagnetic dynamic hysteresis when trained with a limited amount of data, showing the model’s potential in the field of materials science. Full article
(This article belongs to the Special Issue Modeling and Characterization of Magnetic Materials)
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