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The movement of magnetic beads due to a magnetic field gradient is of great interest in different application fields. In this report we present a technique based on a magnetic tweezers setup to measure the velocity factor of magnetically actuated individual superparamagnetic beads in a fluidic environment. Several beads can be tracked simultaneously in order to gain and improve statistics. Furthermore we show our results for different beads with hydrodynamic diameters between 200 and 1000 nm from diverse manufacturers. These measurement data can, for example, be used to determine design parameters for a magnetic separation system, like maximum flow rate and minimum separation time, or to select suitable beads for fixed experimental requirements.
Magnetic nanoparticles (MNP) serve as imaging tracers, therapeutic heating agents and biosensors in biomedical applications. All the above applications rely upon the particles’ unique relaxation mechanisms, which lead to phase shifts in alternating magnetic fields and dissipation. As MNP have an intrinsic size distribution and their magnetic properties are also size-dependent, search is ongoing for the optimally sized MNP that could potentially serve for all three applications simultaneously. In this work, we present our current results on simulating the influence of core size, mono- and polydisperse size distributions as well as magnetic anisotropy on the performance of MNP for both heating and biosensing using micromagnetic dynamic magnetization simulations.
Magnetic nanoparticles (MNP) are investigated with great interest for biomedical applications in diagnostics (e.g. imaging: magnetic particle imaging (MPI)), therapeutics (e.g. hyperthermia: magnetic fluid hyperthermia (MFH)) and multi-purpose biosensing (e.g. magnetic immunoassays (MIA)). What all of these applications have in common is that they are based on the unique magnetic relaxation mechanisms of MNP in an alternating magnetic field (AMF). While MFH and MPI are currently the most prominent examples of biomedical applications, here we present results on the relatively new biosensing application of frequency mixing magnetic detection (FMMD) from a simulation perspective. In general, we ask how the key parameters of MNP (core size and magnetic anisotropy) affect the FMMD signal: by varying the core size, we investigate the effect of the magnetic volume per MNP; and by changing the effective magnetic anisotropy, we study the MNPs’ flexibility to leave its preferred magnetization direction. From this, we predict the most effective combination of MNP core size and magnetic anisotropy for maximum signal generation.
Magnetic nanoparticles (MNP) enable new biomedical applications as imaging tracers, heating agents or biosensors due to their unique relaxation mechanism in alternating magnetic fields. For assessing MNP suitable for such applications, magnetic particle spectroscopy (MPS) offers a reliable method, dual-frequency excitation adding sensitivity. Biomedical applications, however, rely on MNP use in physiological environments (blood, tissue, etc.) of various viscosities, which could strongly alter the MNP relaxation behavior. In this work, we present our preliminary results of varying viscosity on the relaxation of MNP during dual-frequency MPS, studied with micromagnetic dynamic magnetization simulation.
Magnetic Particle Spectroscopy (MPS) allows for direct characterization of magneto-physical properties of magnetic nanoparticles (MNP), which are widely researched as imaging tracers, biosensing units and therapeutic heating agents. All these applications rely primarily on the core size-dependent magnetic particle relaxation dynamics. Therefore, knowledge about core size of any MNP sample is crucial. Dual-frequency MPS increases the characterization potential by considering frequency mixing terms of the received signal of MNP, from which their sizes can be approximated. In this work, preliminary feasibility and interpretation of a proposed size reconstruction method is tested against precisely simulated input data from stochastically coupled Néel-Brownian relaxation modeling using Monte Carlo implementation.
Magnetic nanoparticles (MNP) are widely investigated for biomedical applications in diagnostics (e.g. imaging), therapeutics (e.g. hyperthermia) and general biosensing. For all these applications, the MNPs’ unique magnetic relaxation mechanism in an alternating magnetic field (AFM) is stimulated to induce desired effects. Whereas magnetic fluid hyperthermia (MFH) and magnetic particle imaging (MPI) are the most prominent examples for biomedical application, we investigate the relatively new biosensing application of frequency mixing magnetic detection (FMMD) from a fundamental perspective. Generally, we ask how specific MNP parameters (core size, magnetic anisotropy) influence the signal, specifically we predict the most effective MNP core size for signal generation. In FMMD, simultaneously two AFM are applied: a low-frequency magnetic driving field, driving MNP close to saturation, and a high-frequency excitation field that probes MNP susceptibility: . Resulting from the nonlinear magnetization of the MNP, harmonics of both individual incident frequencies as well as intermodulation products of these frequencies are generated. In this work, we present numerical Monte-Carlo(MC)-based simulations of the MNP relaxation process, solving the Landau-Lifshitz-Gilbert (LLG) equation to predict FMMD signals: As Figure 1 shows for the first four intermodulation signals , with , we can clearly see that larger core sizes generally increase the signal intensity. Same trend is predicted by a simple Langevin-function based thermal equilibrium model. Both predictions include a lognormal size distribution. The effect of core size distribution presumably dominates the effect of magnetic anisotropy. The findings are supported by comparison with experimental data and help to identify which MNP are best suited for magnetic biosensing applications using FMMD.
Frequency mixing magnetic detection (FMMD) is a sensitive and selective technique to detect magnetic nanoparticles (MNPs) serving as probes for binding biological targets. Its principle relies on the nonlinear magnetic relaxation dynamics of a particle ensemble interacting with a dual frequency external magnetic field. In order to increase its sensitivity, lower its limit of detection and overall improve its applicability in biosensing, matching combinations of external field parameters and internal particle properties are being sought to advance FMMD. In this study, we systematically probe the aforementioned interaction with coupled Néel–Brownian dynamic relaxation simulations to examine how key MNP properties as well as applied field parameters affect the frequency mixing signal generation. It is found that the core size of MNPs dominates their nonlinear magnetic response, with the strongest contributions from the largest particles. The drive field amplitude dominates the shape of the field-dependent response, whereas effective anisotropy and hydrodynamic size of the particles only weakly influence the signal generation in FMMD. For tailoring the MNP properties and parameters of the setup towards optimal FMMD signal generation, our findings suggest choosing large particles of core sizes dc > 25 nm nm with narrow size distributions (σ < 0.1) to minimize the required drive field amplitude. This allows potential improvements of FMMD as a stand-alone application, as well as advances in magnetic particle imaging, hyperthermia and magnetic immunoassays.
Frequency mixing magneticdetection(FMMD) has been widely utilized as a measurement technique in magnetic immunoassays. It can also be used for characterization[1]and distinction[2](also known as “colorization”) ofdifferent types of magnetic nanoparticlesaccording totheircore sizes.It is well known that the large particles contribute most of the FMMD signal. Typically, 90% of the signal stems from the largest 10% of the particles [1]. This leads to ambiguities in core size fitting since thecontribution of thesmall sized particles is almostundetectable among the strong responses from the large ones. In this work, we report on how this ambiguity can be overcome. Magnetic nanoparticle samples from Micromod (Rostock, Germany) were prepared in liquid and filterbound state. Their FMMD response at mixing frequencies f1 ± nf2 to magnetic excitation H(t)=H0+H1sin(2 f1t)+H2sin(2 f2t),with H1=1.3mT/μ0 at f1=40.5kHzandH2=16mT/μ0 at f2=63Hz,was measured as a function ofoffset field strength H0= (0,…,24) mT/μ0.The signal calculated fromLangevin model in thermodynamic equilibrium[1]with a lognormal core size distribution fL(dc,d0, ,A) = Aexp(–ln²(dc/d0)/(2 ²))/(dc (2 )1/2)was fitted to the experimental data. For each choice of median diameter d0, pairs of parameters ( ,A) are found which yield excellent fit results with R²>0.99.All the lognormal core size distributions shown in Figure (a) are compatible with the measurements because their large-size tails are almost equal. However, all distributions have different number of particles and different total iron content. We determined the samples’ total iron mass with inductively coupled plasma optical emission spectrometry(ICP-OES) and, out of all possible lognormal distributions, determined the one with the same amount of iron. With this additional externally measured parameter, we resolved the ambiguity in core size distribution and determined the parameters (d0, ,A).
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.
For performing point-of-care molecular diagnostics, magnetic immunoassays constitute a promising alternative to established enzyme-linked immunosorbent assays (ELISA) because they are fast, robust and sensitive. Simultaneous detection of multiple biomolecular targets from one body fluid sample is desired. The aim of this work is to show that multiplex magnetic immunodetection based on magnetic frequency mixing by means of modular immunofiltration columns prepared for different targets is feasible. By calculations of the magnetic response signal, the required spacing between the modules was determined. Immunofiltration columns were manufactured by 3D printing and antibody immobilization was performed in a batch approach. It was shown experimentally that two different target molecules in a sample solution could be individually detected in a single assaying step with magnetic measurements of the corresponding immobilization filters. The arrangement order of the filters and of a negative control did not influence the results. Thus, a simple and reliable approach to multi-target magnetic immunodetection was demonstrated.
