Book/Dissertation / PhD Thesis

FZJ-2023-04615

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Frequency mixing magnetic detection for characterization and multiplex detection of superparamagnetic nanoparticles

Pourshahidi, A. M. (Corresponding author)FZJ*

2023
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag Jülich
ISBN: 978-3-95806-727-1

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Please use a persistent id in citations: urn:nbn:de:0001-20240124094141120-4408806-7  doi:10.34734/FZJ-2023-04615

Abstract: Magnetic immunoassays (MIA) are gaining interest in modern bioanalytical methods. A readout method employed for detection of superparamagnetic biomarkers is based on the principles of magnetic particle spectroscopy. The method of Frequency Mixing magnetic Detection (FMMD) involves the excitation of magnetic nanoparticles (MNPs) using a dual frequency alternating magnetic field. MIA methods using FMMD as detection principle have shown a high potential to be used in point-of-care testing. On the other hand, it is often desired in biosensing to perform multiplex detection, that is the measurement of two or more analytes within a single sample. For methods employing magnetic particle as markers, this means the ability to simultaneously detect different types of magnetic particle in one sample. This thesis initially reports on the required FMMD instrumentation and its latest developments, including a duty-cycle power management strategy and a permanent ring magnet offset module to reduce the adverse effect of temperature variations on measured signals. We discuss the measured phase of the FMMD signal. We elaborate on the influencing factors and their effects using numerical simulation of the signals, and verify the effects through experimental measurements.Moreover, we present a method for discerning the contributions of different MNPs in binary and ternary mixtures by an analysis of their static offset magnetic field-dependent FMMD signals. The mixture samples were analyzed by identifying the best linear combination of the measured reference signals of the pure constituents that best resembled the measured signals of the mixtures. The mixing ratios could be determined with an accuracy of better than 14%. One of the important properties of MNP that has an influence on the FMMD signals is the size of their magnetic core. The FMMD technique can be used to characterize the MNP. However, it has been shown that the largest particles in the sample contribute most of the FMMD signal. This leads to ambiguities in core size determination from mathematical fitting, since the contribution of the small-sized particles is almost undetectable among the strong responses from the large ones. In this thesis, we discuss how to address this ambiguity by modelling thesignal intensity using the Langevin model in thermodynamic equilibrium, which includes a lognormal core size distribution fitted to experimentally measured FMMD data of immobilized MNPs. With the help of an independent determination of the samples’ total iron mass, for instance from inductively coupled plasma optical emission spectrometry, we are able to unambiguously identify the particles’ lognormal core size distribution. The technique has great potential to serve as characterization tool for quality control in MNP synthesis and applications.

Note: Dissertation, RWTH Aachen University, 2023

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Contributing Institute(s):

1. Bioelektronik (IBI-3)

Research Program(s):

1. 5241 - Molecular Information Processing in Cellular Systems (POF4-524) (POF4-524)

Appears in the scientific report 2023

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