Enhanced magnetic moment discrimination for multiplex nanoparticle quantification via dual-frequency nonlinearity probing
Communications Engineering, vol. 5
Abstract
Advanced applications of Magnetic nanoparticles (MNPs) in biomedicine based on multiplex MNP distinction require accurate, model-agnostic characterization of their magnetic moment distributions (MMDs). However, the resolving power of conventional MMD reconstruction from a static magnetization curve remains literarily underexplored. Moreover, due to particle-particle interactions, the response of the particle mixture might differ from the linear combination of the original constituents. We explore resolution enhancement in magnetic-moment space by directly probing higher-order magnetization derivatives, benefiting from their ever-increasing field-domain localization. Nonetheless, the direct derivative probing, as it is inevitably conducted dynamically, poses an interpretive problem for the origin of the nonlinearities. Spectral symmetries arising solely under dual-frequency excitation reflect the corresponding origins of amplitude- and rate-related nonlinearities. Using a dedicated experimental setup capable of synchronous demodulation of intermodulation terms, the method is tested on commercial MNP samples and benchmarked with conventional AC-susceptometry and static magnetization data. The binary mixture ratio was quantified with 8.9% deviation, without any prior information about the initial constituents differing by a factor of 3 in their average magnetic moments, potentially allowing the accommodation of three independent contrast channels for multiplex MNP applications as well as qualitatively probing magnetic interaction effects.
Authors 4
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Forschungszentrum Jülich · RWTH Aachen University
Affiliation as printed
Faculty of Mathematics, Computer Sci. and Natural Sci., RWTH Aachen University, Aachen, Germany. timur.bikulov@rwth-aachen.de
Institute of Biological Information Processing, Forschungszentrum Jülich, Jülich, Germany. timur.bikulov@rwth-aachen.de
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Affiliation as printed
Department of Medical Engineering and Applied Mathematics, FH Aachen University of Applied Sciences, Jülich, Germany
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Forschungszentrum Jülich · RWTH Aachen University
Affiliation as printed
Faculty of Mathematics, Computer Sci. and Natural Sci., RWTH Aachen University, Aachen, Germany
Institute of Biological Information Processing, Forschungszentrum Jülich, Jülich, Germany
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Forschungszentrum Jülich · FH Aachen
Affiliation as printed
Department of Medical Engineering and Applied Mathematics, FH Aachen University of Applied Sciences, Jülich, Germany. h.-j.krause@fz-juelich.de
Institute of Biological Information Processing, Forschungszentrum Jülich, Jülich, Germany. h.-j.krause@fz-juelich.de
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