Research on Spatial Localization Method of Magnetic Nanoparticle Samples Based on Second Harmonic Waves

Existing magnetic tracer detection systems primarily rely on fundamental wave signal acquisition using non-differential sensor configurations. These sensors are highly susceptible to external interference and lack tomographic localization capabilities, hindering their clinical application. To address these limitations, this paper presents a novel method for achieving the deep spatial localization of tracers. The method exploits second harmonic signal detection at non-zero field points. By considering the combined nonlinear characteristics of the coil's axial spatial magnetic field distribution and the Langevin function, a correlation model linking the signal peak and bias field is established. This model enables the determination of the tracer's precise spatial location. Building on this framework, a handheld device for localizing magnetic nanoparticle tracers was developed. The device harnesses the second harmonic response generated by coupling an AC excitation field with a DC bias field. Our findings demonstrate that under conditions of reduced coil turns and weak excitation fields, the DC bias field exhibits exclusive dependence on the axial distance of the detection point, independent of particle concentration. This implies that the saturated DC bias field corresponding to the second harmonic signal can be used to determine the magnetic nanoparticle sample detection depth. The experimental results validated the method's high accuracy, with axial detection distance and concentration reduction errors of only 4.8% and 4.1%, respectively. This research paves the way for handheld probes capable of tomographic tracer detection, offering a novel approach for advancing magnetically sensitive biomedical detection technologies.

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Publication Details

Journal
Micromachines
Published
2024-09-30
DOI
https://doi.org/10.3390/mi15101218
Citations
1
Primary Topic
Characterization and Applications of Magnetic Nanoparticles
Type
article
Field-Weighted Citation Impact
0.18

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Research on Spatial Localization Method of Magnetic Nanoparticle Samples Based on Second Harmonic Waves

Huang Ping, Yue Li, Fuyin Zheng, Zheyan Wang et al.
1 citations
Micromachines
Characterization and Applications of Magnetic Nanoparticles
0.18
article

Research on Spatial Localization Method of Magnetic Nanoparticle Samples Based on Second Harmonic Waves

Huang Ping, Yue Li, Fuyin Zheng, Zheyan Wang, Shi Bai, Zhiyao Liu, Zhichuan Qiu, Hongli Yu, Lingke Gai
article en
1 citations

Abstract

Existing magnetic tracer detection systems primarily rely on fundamental wave signal acquisition using non-differential sensor configurations. These sensors are highly susceptible to external interference and lack tomographic localization capabilities, hindering their clinical application. To address these limitations, this paper presents a novel method for achieving the deep spatial localization of tracers. The method exploits second harmonic signal detection at non-zero field points. By considering the combined nonlinear characteristics of the coil's axial spatial magnetic field distribution and the Langevin function, a correlation model linking the signal peak and bias field is established. This model enables the determination of the tracer's precise spatial location. Building on this framework, a handheld device for localizing magnetic nanoparticle tracers was developed. The device harnesses the second harmonic response generated by coupling an AC excitation field with a DC bias field. Our findings demonstrate that under conditions of reduced coil turns and weak excitation fields, the DC bias field exhibits exclusive dependence on the axial distance of the detection point, independent of particle concentration. This implies that the saturated DC bias field corresponding to the second harmonic signal can be used to determine the magnetic nanoparticle sample detection depth. The experimental results validated the method's high accuracy, with axial detection distance and concentration reduction errors of only 4.8% and 4.1%, respectively. This research paves the way for handheld probes capable of tomographic tracer detection, offering a novel approach for advancing magnetically sensitive biomedical detection technologies.

MicromachinesVol. 15(10)
Shenyang University of Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Liaoning Province, National Key Research and Development Program of China
Openalex Percentile: Top 52%
Characterization and Applications of Magnetic Nanoparticles
0.18
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