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Advances in Electromagnetic Properties of Materials and Related Nondestructive Testing

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A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Advanced Materials Characterization".

Deadline for manuscript submissions: closed (20 May 2022) | Viewed by 12834

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Special Issue Editor

Prof. Dr. Przemyslaw Lopato

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Guest Editor

Laboratory of Antennas and High Frequency Techniques, Department of Electrical and Computer Engineering, West Pomeranian University of Technology, 70-310 Szczecin, Poland
Interests: nondestructive evaluation using electromagnetic methods; microwave sensors; terahertz sensors; eddy current sensors; metasurfaces; terahertz TDS; dielectric properties measurements

Special Issue Information

Dear Colleagues,

The electromagnetic (EM) properties of materials and the related nondestructive testing methods have for many years increasingly attracted the attention of industry engineers and scientists. We are currently observing the intense work carried out in research and development centers around the world on new composite materials, steel and polymer structures, or artificial (engineered) materials with unusual electromagnetic properties. New structures, as well as traditional ones, are finding more and more diverse applications and creating the possibility of constructing new electromagnetic devices, especially in wave problems (microwave, terahertz, IR, and visible frequency bands). This leads to the need to determine and test the electric and magnetic properties of the developed structures, as well as to test their continuity and detect possible inhomogeneity in a wide frequency range—from static fields to the ultraviolet band.

This Special Issue is devoted to advances in electromagnetic properties of materials in the wide frequency range (DC, low frequency, microwave, terahertz, IR). It refers to broad topics considering new structures, models, measuring concepts and systems, transducers, influence of external phenomena on electromagnetic properties, error and distortion analysis, and elimination of their sources in EM properties’ estimation.

This Special Issue will also focus on various methods of electromagnetic nondestructive testing, including well-established AC-magnetization-based methods, eddy current, microwave, terahertz methods, IR thermography, and slightly less common, but very valuable techniques such as dielectric spectroscopy, ferromagnetic resonance, and others.

It is my pleasure to invite you to submit a manuscript to this Special Issue. Full papers, communications, and reviews are all welcome.

Prof. Dr. Przemyslaw Lopato
Guest Editor

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

dielectric properties
polymer dielectrics
dielectric spectroscopy
magnetic properties
ferromagnetic resonance
electromagnetic metamaterials and metasurfaces
composite structures
terahertz spectroscopy
electromagnetic nondestructive evaluation
electromagnetic properties sensors
electromagnetic properties of biomaterials

Published Papers (6 papers)

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Research

22 pages, 8857 KiB

Open AccessArticle

An Evaluation of 3D-Printed Materials’ Structural Properties Using Active Infrared Thermography and Deep Neural Networks Trained on the Numerical Data

by Barbara Szymanik

Materials 2022, 15(10), 3727; https://doi.org/10.3390/ma15103727 - 23 May 2022

Cited by 3 | Viewed by 1638

Abstract

This article describes an approach to evaluating the structural properties of samples manufactured through 3D printing via active infrared thermography. The mentioned technique was used to test the PETG sample, using halogen lamps as an excitation source. First, a simplified, general numerical model of the phenomenon was prepared; then, the obtained data were used in a process of the deep neural network training. Finally, the network trained in this manner was used for the material evaluation on the basis of the original experimental data. The described methodology allows for the automated assessment of the structural state of 3D−printed materials. The usage of a generalized model is an innovative method that allows for greater product assessment flexibility. Full article

(This article belongs to the Special Issue Advances in Electromagnetic Properties of Materials and Related Nondestructive Testing)

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15 pages, 5082 KiB

Open AccessArticle

Influence of Varying Tensile Stress on Domain Motion

by Kun Zeng, Guiyun Tian, Jia Liu, Bin Gao, Yi Liu and Qianhang Liu

Materials 2022, 15(9), 3399; https://doi.org/10.3390/ma15093399 - 09 May 2022

Cited by 4 | Viewed by 1384

Abstract

Magnetic domain motion has been widely studied in the fields of spintronics, nanowires, and thin films. However, there is a lack of such studies on industrial steels, especially for domain motion under the action of varying stress. Understanding domain motion under stress is helpful for the improvement of evaluation accuracy and the establishment of theoretical models of passive, nondestructive testing technology. This paper presents the influence of varying tensile stresses on the magnetic domain motion of silicon steel sheets. Magnetic domain rotation and domain wall displacement were characterized using magnetic domain images, and their motion mechanisms under elastic and plastic stresses are presented. The results show that the domain rotation under stress involves reversible and irreversible changes. The effect of material rearrangement on domain rotation and domain wall displacement after plastic deformation is discussed. Based on the motion mechanism, a threshold stress value (TSV) required for the complete disappearance of the supplementary domains in the elastic range is proposed, enabling the classification of the elastic stress ranges in which the reversible and irreversible domain rotations occur. In addition, the effect of microstructure on TSV is also discussed, and the results show that the regions far away from the grain boundary need larger stresses to complete an irreversible domain rotation. Additionally, the domain width and orientation also affect the TSV. These findings regarding the domain motion mechanism and TSV can help to explain the sequence of domain rotation under stress and modify the stress assessment under dynamic loads in electromagnetic nondestructive evaluation, especially in the magnetic memory method. Full article

(This article belongs to the Special Issue Advances in Electromagnetic Properties of Materials and Related Nondestructive Testing)

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10 pages, 3357 KiB

Open AccessArticle

Application of a Single Cell Electric-SRR Metamaterial for Strain Evaluation

by Michal Herbko and Przemyslaw Lopato

Materials 2022, 15(1), 291; https://doi.org/10.3390/ma15010291 - 31 Dec 2021

Cited by 4 | Viewed by 1816

Abstract

Strain is a crucial assessment parameter in structural health monitoring systems. Microstrip sensors have been one of the new types of sensors used to measure this parameter in recent years. So far, the strain directionality of these sensors and the methods of miniaturization have been studied. This article proposes the use of a single cell metamaterial as a resonator of the microstrip sensor excited through the microstrip line. The proposed solution allowed for significant miniaturization of the microstrip sensor, with just a slight decrease in sensitivity. The proposed sensor can be used to measure local deformation values and in places with a small access area. The presented sensor was validated using numerical and experimental methods. In addition, it was compared with a reference (rectangular geometry) microstrip sensor. Full article

(This article belongs to the Special Issue Advances in Electromagnetic Properties of Materials and Related Nondestructive Testing)

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19 pages, 8931 KiB

Open AccessArticle

Identification of Grain Oriented SiFe Steels Based on Imaging the Instantaneous Dynamics of Magnetic Barkhausen Noise Using Short-Time Fourier Transform and Deep Convolutional Neural Network

by Michal Maciusowicz, Grzegorz Psuj and Paweł Kochmański

Materials 2022, 15(1), 118; https://doi.org/10.3390/ma15010118 - 24 Dec 2021

Cited by 4 | Viewed by 2222

Abstract

This paper presents a new approach to the extraction and analysis of information contained in magnetic Barkhausen noise (MBN) for evaluation of grain oriented (GO) electrical steels. The proposed methodology for MBN analysis is based on the combination of the Short-Time Fourier Transform for the observation of the instantaneous dynamics of the phenomenon and deep convolutional neural networks (DCNN) for the extraction of hidden information and building the knowledge. The use of DCNN makes it possible to find even complex and convoluted rules of the Barkhausen phenomenon course, difficult to determine based solely on the selected features of MBN signals. During the tests, several samples made of conventional and high permeability GO steels were tested at different angles between the rolling and transverse directions. The influences of the angular resolution and the proposed additional prediction update algorithm on the DCNN accuracy were investigated, obtaining the highest gain for the angle of 3.6°, for which the overall accuracy exceeded 80%. The obtained results indicate that the proposed new solution combining time–frequency analysis and DCNN for the quantification of information from MBN having stochastic nature may be a very effective tool in the characterization of the magnetic materials. Full article

(This article belongs to the Special Issue Advances in Electromagnetic Properties of Materials and Related Nondestructive Testing)

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10 pages, 3459 KiB

Open AccessArticle

Far-Field Subwavelength Straight-Line Projection/Imaging by Means of a Novel Double-Near-Zero Index-Based Two-Layer Metamaterial

by Reza Dehbashi, Taras Plakhotnik and Timo A. Nieminen

Materials 2021, 14(19), 5484; https://doi.org/10.3390/ma14195484 - 22 Sep 2021

Cited by 1 | Viewed by 2275

Abstract

In this paper, for the first time, tuned near-zero-index materials are used in a structure for the long-distance projection of very closely spaced objects with subwavelength separation. Near-zero-index materials have never been used for subwavelength projection/imaging. The proposed novel structure is composed of a two-layer slab that can project two slits with a subwavelength separation distance to a long distance without diverged/converged interference of the two imaged waves. The two-layer slab consists of a thin double-near-zero (DNZ) slab with an obtained tuned index of 0.05 and thickness of 0.04λ₀ coupled with a high-index dielectric slab with specific thicknesses. Through a parametric study, the non-zero index of the DNZ layer is tuned to create a clear image when it is coupled with the high-index dielectric layer. The minimum size for the aperture of the proposed two-layer slab is 2λ₀ to provide a clear projection of the two slits. The space between the slits is λ₀/8, which is five times beyond the diffraction limit. It is shown that, through the conventional methods (e.g., only with high-index dielectric slabs, uncoupled with a DNZ layer), it is impossible to clearly project slits at a large distance (~λ₀) due to the diffraction limit. An analytical analysis, as well as numerical results in a finite-element-based simulator, confirm the function of the proposed structure. Full article

(This article belongs to the Special Issue Advances in Electromagnetic Properties of Materials and Related Nondestructive Testing)

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22 pages, 85963 KiB

Open AccessArticle

Detection and Identification of Defects in 3D-Printed Dielectric Structures via Thermographic Inspection and Deep Neural Networks

by Barbara Szymanik, Grzegorz Psuj, Maryam Hashemi and Przemyslaw Lopato

Materials 2021, 14(15), 4168; https://doi.org/10.3390/ma14154168 - 27 Jul 2021

Cited by 16 | Viewed by 2609

Abstract

In this paper, we propose a new method based on active infrared thermography (IRT) applied to assess the state of 3D-printed structures. The technique utilized here—active IRT—assumes the use of an external energy source to heat the tested material and to create a temperature difference between undamaged and defective areas, and this temperature difference is possible to observe with a thermal imaging camera. In the case of materials with a low value of thermal conductivity, such as the acrylonitrile butadiene styrene (ABS) plastic printout tested in the presented work, the obtained temperature differences are hardly measurable. Hence, the proposed novel IRT method is complemented by a dedicated algorithm for signal analysis and a multi-label classifier based on a deep convolutional neural network (DCNN). For the initial testing of the presented methodology, a 3D printout made in the shape of a cuboid was prepared. One type of defect was tested—surface breaking holes of various depths and diameters that were produced artificially by inclusion in the printout. As a result of examining the sample via the IRT method, a sequence of thermograms was obtained, which enabled the examination of the temporal representation of temperature variation over the examined region of the material. First, the obtained signals were analysed using a new algorithm to enhance the contrast between the background and the defect areas in the 3D print. In the second step, the DCNN was utilised to identify the chosen defect parameters. The experimental results show the high effectiveness of the proposed hybrid signal analysis method to visualise the inner structure of the sample and to determine the defect and size, including the depth and diameter. Full article

(This article belongs to the Special Issue Advances in Electromagnetic Properties of Materials and Related Nondestructive Testing)

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