Magnetoimpedance (MI) biosensors for the detection of in-tissue incorporated magnetic nanoparticles are a subject of special interest. The possibility of the detection of the ferrogel samples mimicking the natural tissues with nanoparticles was proven previously for symmetric MI thin-film multilayers. In this work, in order to describe the MI effect in non-symmetric multilayered elements covered by ferrogel layer we propose an electromagnetic model based on a solution of the 4Maxwell equations. The approach is based on the previous calculations of the distribution of electromagnetic fields in the non-symmetric multilayers further developed for the case of the ferrogel covering. The role of the asymmetry of the film on the MI response of the multilayer-ferrogel structure is analyzed in the details. The MI field and frequency dependences, the concentration dependences of the MI for fixed frequencies and the frequency dependence of the concentration sensitivities are obtained for the detection process by both symmetric and non-symmetric MI structures.
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http://dx.doi.org/10.3390/s21155151 | DOI Listing |
Sensors (Basel)
June 2024
Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620002, Russia.
The recently proposed magnetoimpedance tomography method is based on the analysis of the frequency dependences of the impedance measured at different external magnetic fields. The method allows one to analyze the distribution of magnetic properties over the cross-section of the ferromagnetic conductor. Here, we describe the example of theoretical study of the magnetoimpedance effect in an amorphous microwire with inhomogeneous magnetic structure.
View Article and Find Full Text PDFJ Phys Condens Matter
May 2024
Departamento de Física, Universidade federal de Santa Maria, Santa Maria, RS 97105-900, Brazil.
Magnetic systems with competing anisotropies generally exhibit asymmetry between the maximum amplitudes of the right and left maxima in a magnetoimpedance curve. Small errors in positioning the samples at the experimental setup may also produce such asymmetry. In this work, we present a study on the sources of the asymmetry between magnetoimpedance peaks in systems that present the exchange bias phenomenon, by comparing a phenomenological model to experimental data.
View Article and Find Full Text PDFSensors (Basel)
November 2023
Ingenium College of Liberal Arts, Kwangwoon University, 20 Kwangwoon-ro, Seoul 01897, Republic of Korea.
Deep learning technology is generally applied to analyze periodic data, such as the data of electromyography (EMG) and acoustic signals. Conversely, its accuracy is compromised when applied to the anomalous and irregular nature of the data obtained using a magneto-impedance (MI) sensor. Thus, we propose and analyze a deep learning model based on recurrent neural networks (RNNs) optimized for the MI sensor, such that it can detect and classify data that are relatively irregular and diverse compared to the EMG and acoustic signals.
View Article and Find Full Text PDFSensors (Basel)
December 2022
Department of Physics, Pedagogical Institute, Irkutsk State University, 664003 Irkutsk, Russia.
A description of the method of magnetoimpedance tomography is presented. This method is based on the analysis of the frequency dependences of the impedance obtained in magnetic fields of various strengths. It allows one to determine the distribution of electrical and magnetic properties over the cross-section of the conductor, as well as their dependence on the magnetic field.
View Article and Find Full Text PDFSensors (Basel)
October 2021
Department of Physics, Pedagogical Institute, Irkutsk State University, 664003 Irkutsk, Russia.
Soft magnetic materials are widely requested in electronic and biomedical applications. Co-based amorphous ribbons are materials which combine high value of the magnetoimpedance effect (MI), high sensitivity with respect to the applied magnetic field, good corrosion stability in aggressive environments, and reasonably low price. Functional properties of ribbon-based sensitive elements can be modified by deposition of additional magnetic and non-ferromagnetic layers with required conductivity.
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