These MRX based measurement and analysis procedures have substantially supported the development of MNP based biomedical applications.

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Magnetic nanoparticles have proven to be extremely useful in a broad range of biomedical applications. To ensure optimal efficiency, a precise characterization of these particles is required. Thermal Noise Magnetrometry (TNM) is a recently developed characterization technique that has already been validated against other techniques. TNM offers a unique advantage in that no external excitation of the system is required to drive the measurement. However, the extremely small stochastic signal in the fT range currently limits the accessibility of the method, and a better understanding of the influences of the sample characteristics on the TNM signal is necessary. In this study, we present a theoretical framework to model the magnetic noise power properties of particle ensembles and their signal as measured via TNM. Both intrinsic sample properties (such as the number of particles or their volume) and the geometrical properties of the sample in the setup have been investigated numerically and validated with experiments. It is shown that the noise power depends linearly on the particle concentration, quadratically on the individual particle size, and linearly on the particle size for a constant total amount of magnetic material in the sample. Furthermore, an optimized sample shape is calculated for the given experimental geometry and subsequently 3d printed, giving rise to an 3.5 fold increase in TNM signal from approximately 0.007 to 0.026 pT 2 with less than half of the magnetic material.

Magnetic nanoparticles (MNPs) exhibit unique magnetic properties making them ideally suited for a variety of biomedical applications. Depending on the desired magnetic effect, MNPs must meet special magnetic requirements which are mainly determined by their structural properties (e.g., size distribution). The hyphenation of chromatographic separation techniques with complementary detectors is capable of providing multidimensional information of submicron particles. Although various methods have already been combined for this approach, so far, no detector for the online magnetic analysis was used. Magnetic particle spectroscopy (MPS) has been proven a straightforward technique for specific quantification and characterization of MNPs. It combines high sensitivity with high temporal resolution; both of these are prerequisites for a successful hyphenation with chromatographic separation. We demonstrate the capability of MPS to specifically detect and characterize MNPs under usually applied asymmetric flow field-flow fractionation (A4F) conditions (flow rates, MNP concentration, different MNP types). To this end MPS has been successfully integrated into an A4F multidetector platform including dynamic ligth scattering (DLS), multi-angle light scattering (MALS) and ultraviolet (UV) detection. Our system allows for rapid and comprehensive characterization of typical MNP samples for the systematic investigation of structure-dependent magnetic properties. This has been demonstrated by magnetic analysis of the commercial magnetic resonance imaging (MRI) contrast agent Ferucarbotran (FER) during hydrodynamic A4F fractionation. OPEN ACCESSChromatography 2015, 2 656