Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique

In this work, the core size estimation technique of magnetic nanoparticles (MNPs) using the static magnetization curve obtained from a high-Tc SQUID magnetometer and a metaheuristic inversion technique based on the Particle Swarm Optimizer (PSO) algorithm is presented. The high-Tc SQUID magnetometer...

Full description

Bibliographic Details
Main Authors: Mohd Mawardi, Saari, Mohd Herwan, Sulaiman, Kiwa, Toshihiko
Format: Article
Language:English
Published: The Institute of Electronics, Information and Communication Engineers 2023
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/40057/1/Estimation%20of%20Core%20Size%20Distribution%20of%20Magnetic%20Nanoparticles.pdf
_version_ 1825815412790525952
author Mohd Mawardi, Saari
Mohd Herwan, Sulaiman
Kiwa, Toshihiko
author_facet Mohd Mawardi, Saari
Mohd Herwan, Sulaiman
Kiwa, Toshihiko
author_sort Mohd Mawardi, Saari
collection UMP
description In this work, the core size estimation technique of magnetic nanoparticles (MNPs) using the static magnetization curve obtained from a high-Tc SQUID magnetometer and a metaheuristic inversion technique based on the Particle Swarm Optimizer (PSO) algorithm is presented. The high-Tc SQUID magnetometer is constructed from a high-Tc SQUID sensor coupled by a flux transformer to sense the modulated magnetization signal from a sample. The magnetization signal is modulated by the lateral vibration of the sample on top of a planar differential detection coil of the flux transformer. A pair of primary and excitation coils are utilized to apply an excitation field parallel to the sensitive axis of the detection coil. Using the high-Tc SQUID magnetometer, the magnetization curve of a commercial MNP sample (Resovist) was measured in a logarithmic scale of the excitation field. The PSO inverse technique is then applied to the magnetization curve to construct the magnetic moment distribution. A multimodal normalized log-normal distribution was used in the minimization of the objective function of the PSO inversion technique, and a modification of the PSO search region is proposed to improve the exploration and exploitation of the PSO particles. As a result, a good agreement on the Resovist magnetic core size was obtained between the proposed technique and the non-negative least square (NNLS) inversion technique. The estimated core sizes of 8.0484 nm and 20.3018 nm agreed well with the values reported in the literature using the commercial low-Tc SQUID magnetometer with the SVD and NNLS inversion techniques. Compared to the NNLS inversion technique, the PSO inversion technique had merits in exploring an optimal core size distribution freely without being regularized by a parameter and facilitating an easy peak position determination owing to the smoothness of the constructed distribution. The combination of the high-Tc SQUID magnetometer and the PSO-based reconstruction technique offers a powerful approach for characterizing the MNP core size distribution, and further improvements can be expected from the recent state-of-the-art optimization algorithm to optimize further the computation time and the best objective function value.
first_indexed 2024-03-06T13:13:06Z
format Article
id UMPir40057
institution Universiti Malaysia Pahang
language English
last_indexed 2024-03-06T13:13:06Z
publishDate 2023
publisher The Institute of Electronics, Information and Communication Engineers
record_format dspace
spelling UMPir400572024-01-17T06:15:00Z http://umpir.ump.edu.my/id/eprint/40057/ Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique Mohd Mawardi, Saari Mohd Herwan, Sulaiman Kiwa, Toshihiko TK Electrical engineering. Electronics Nuclear engineering In this work, the core size estimation technique of magnetic nanoparticles (MNPs) using the static magnetization curve obtained from a high-Tc SQUID magnetometer and a metaheuristic inversion technique based on the Particle Swarm Optimizer (PSO) algorithm is presented. The high-Tc SQUID magnetometer is constructed from a high-Tc SQUID sensor coupled by a flux transformer to sense the modulated magnetization signal from a sample. The magnetization signal is modulated by the lateral vibration of the sample on top of a planar differential detection coil of the flux transformer. A pair of primary and excitation coils are utilized to apply an excitation field parallel to the sensitive axis of the detection coil. Using the high-Tc SQUID magnetometer, the magnetization curve of a commercial MNP sample (Resovist) was measured in a logarithmic scale of the excitation field. The PSO inverse technique is then applied to the magnetization curve to construct the magnetic moment distribution. A multimodal normalized log-normal distribution was used in the minimization of the objective function of the PSO inversion technique, and a modification of the PSO search region is proposed to improve the exploration and exploitation of the PSO particles. As a result, a good agreement on the Resovist magnetic core size was obtained between the proposed technique and the non-negative least square (NNLS) inversion technique. The estimated core sizes of 8.0484 nm and 20.3018 nm agreed well with the values reported in the literature using the commercial low-Tc SQUID magnetometer with the SVD and NNLS inversion techniques. Compared to the NNLS inversion technique, the PSO inversion technique had merits in exploring an optimal core size distribution freely without being regularized by a parameter and facilitating an easy peak position determination owing to the smoothness of the constructed distribution. The combination of the high-Tc SQUID magnetometer and the PSO-based reconstruction technique offers a powerful approach for characterizing the MNP core size distribution, and further improvements can be expected from the recent state-of-the-art optimization algorithm to optimize further the computation time and the best objective function value. The Institute of Electronics, Information and Communication Engineers 2023 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40057/1/Estimation%20of%20Core%20Size%20Distribution%20of%20Magnetic%20Nanoparticles.pdf Mohd Mawardi, Saari and Mohd Herwan, Sulaiman and Kiwa, Toshihiko (2023) Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique. IEICE Transactions on Electronics. pp. 1-8. ISSN 0916-8524. (Published) https://doi.org/10.1587/transele.2023SEP0002 https://doi.org/10.1587/transele.2023SEP0002
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Mohd Mawardi, Saari
Mohd Herwan, Sulaiman
Kiwa, Toshihiko
Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique
title Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique
title_full Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique
title_fullStr Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique
title_full_unstemmed Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique
title_short Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique
title_sort estimation of core size distribution of magnetic nanoparticles using high tc squid magnetometer and particle swarm optimizer based inversion technique
topic TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/40057/1/Estimation%20of%20Core%20Size%20Distribution%20of%20Magnetic%20Nanoparticles.pdf
work_keys_str_mv AT mohdmawardisaari estimationofcoresizedistributionofmagneticnanoparticlesusinghightcsquidmagnetometerandparticleswarmoptimizerbasedinversiontechnique
AT mohdherwansulaiman estimationofcoresizedistributionofmagneticnanoparticlesusinghightcsquidmagnetometerandparticleswarmoptimizerbasedinversiontechnique
AT kiwatoshihiko estimationofcoresizedistributionofmagneticnanoparticlesusinghightcsquidmagnetometerandparticleswarmoptimizerbasedinversiontechnique