Frequency mixing magnetic detection for characterization and multiplex detection of superparamagnetic nanoparticles

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

Core size analysis of magnetic nanoparticles using frequency mixing magnetic detection with a permanent magnet as an offset source

Frequency mixing magnetic detection (FMMD) has been widely used in magnetic immunoassay measurement techniques. It can also be used to characterize and distinguish different magnetic nanoparticle (MNP) types according to their magnetic cores size. In a previous work, a method for resolving ambiguities in determination of the core size distribution was utilized involving measurement of total iron mass. Recently, a new FMMD measurement head was developed in which a pair of permanent ring magnets are used to generate the static offset magnetic field. Here, we show that this new measurement head can be applied for determining the core size distribution of MNP, and compare the results with the outcomes of our conventional electromagnet offset module FMMD

Core size analysis of magnetic nanoparticles using frequency mixing magnetic detection with a permanent magnet as an offset source

Frequency mixing magnetic detection (FMMD) has been widely used in magnetic immunoassay measurement techniques. It can also be used to characterize and distinguish different magnetic nanoparticle (MNP) types according to their magnetic cores size. In a previous work, a method for resolving ambiguities in determination of the core size distribution was utilized involving measurement of total iron mass. Recently, a new FMMD measurement head was developed in which a pair of permanent ring magnets are used to generate the static offset magnetic field. Here, we show that this new measurement head can be applied for determining the core size distribution of MNP, and compare the results with the outcomes of our conventional electromagnet offset module FMMD

Multiplex Detection of Different Magnetic Beads Using Frequency Scanning in Magnetic Frequency Mixing Technique

In modern bioanalytical methods, it is often desired to detect several targets in one sample within one measurement. Immunological methods including those that use superparamagnetic beads are an important group of techniques for these applications. The goal of this work is to investigate the feasibility of simultaneously detecting different superparamagnetic beads acting as markers using the magnetic frequency mixing technique. The frequency of the magnetic excitation field is scanned while the lower driving frequency is kept constant. Due to the particles’ nonlinear magnetization, mixing frequencies are generated. To record their amplitude and phase information, a direct digitization of the pickup-coil’s signal with subsequent Fast Fourier Transformation is performed. By synchronizing both magnetic fields, a stable phase information is gained. In this research, it is shown that the amplitude of the dominant mixing component is proportional to the amount of superparamagnetic beads inside a sample. Additionally, it is shown that the phase does not show this behaviour. Excitation frequency scans of different bead types were performed, showing different phases, without correlation to their diverse amplitudes. Two commercially available beads were selected and a determination of their amount in a mixture is performed as a demonstration for multiplex measurements

Frequency Mixing Magnetic Detection Setup Employing Permanent Ring Magnets as a Static Offset Field Source

Frequency mixing magnetic detection (FMMD) has been explored for its applications in fields of magnetic biosensing, multiplex detection of magnetic nanoparticles (MNP) and the determination of core size distribution of MNP samples. Such applications rely on the application of a static offset magnetic field, which is generated traditionally with an electromagnet. Such a setup requires a current source, as well as passive or active cooling strategies, which directly sets a limitation based on the portability aspect that is desired for point of care (POC) monitoring applications. In this work, a measurement head is introduced that involves the utilization of two ring-shaped permanent magnets to generate a static offset magnetic field. A steel cylinder in the ring bores homogenizes the field. By variation of the distance between the ring magnets and of the thickness of the steel cylinder, the magnitude of the magnetic field at the sample position can be adjusted. Furthermore, the measurement setup is compared to the electromagnet offset module based on measured signals and temperature behavior

Probing particle size dependency of frequency mixing magnetic detection with dynamic relaxation simulation

Biomedical applications of magnetic nanoparticles (MNP) fundamentally rely on the particles’ magnetic relaxation as a response to an alternating magnetic field. The magnetic relaxation complexly depends on the interplay of MNP magnetic and physical properties with the applied field parameters. It is commonly accepted that particle core size is a major contributor to signal generation in all the above applications, however, most MNP samples comprise broad distribution spanning 10 nm and more. Therefore, precise knowledge of the exact contribution of individual core sizes to signal generation is desired for optimal MNP design generally for each application. Specifically, we present a magnetic relaxation simulation-driven analysis of experimental frequency mixing magnetic detection (FMMD) for biosensing to quantify the contributions of individual core size fractions towards signal generation. Applying our method to two different experimental MNP systems, we found the most dominant contributions from approx. 20 nm sized particles in the two independent MNP systems. Additional comparison between freely suspended and immobilized MNP also reveals insight in the MNP microstructure, allowing to use FMMD for MNP characterization, as well as to further fine-tune its applicability in biosensing

Resolving ambiguities in core size determination of magnetic nanoparticles from magnetic frequency mixing data

Frequency mixing magnetic detection (FMMD) has been widely utilized as a measurement technique in magnetic immunoassays. It can also be used for the characterization and distinction (also known as “colourization”) of different types of magnetic nanoparticles (MNPs) based on their core sizes. In a previous work, it was shown that the large particles contribute most of the FMMD signal. This leads to ambiguities in core size determination from fitting since the contribution of the small-sized particles is almost undetectable among the strong responses from the large ones. In this work, we report on how this ambiguity can be overcome by modelling the signal intensity using the Langevin model in thermodynamic equilibrium including a lognormal core size distribution fL(dc,d0,σ) fitted to experimentally measured FMMD data of immobilized MNPs. For each given median diameter d0, an ambiguous amount of best-fitting pairs of parameters distribution width σ and number of particles Np with R² > 0.99 are extracted. By determining the samples’ total iron mass, mFe, with inductively coupled plasma optical emission spectrometry (ICP-OES), we are then able to identify the one specific best-fitting pair (σ, Np) one uniquely. With this additional externally measured parameter, we resolved the ambiguity in core size distribution and determined the parameters (d0, σ, Np) directly from FMMD measurements, allowing precise MNPs sample characterization