Iron oxide nanoparticles are the basic components of the most promising magneto-responsive systems for nanomedicine, ranging from drug delivery and imaging to hyperthermia cancer treatment, as well as to rapid point-of-care diagnostic systems with magnetic nanoparticles. Advanced synthesis procedures of single- and multi-core iron-oxide nanoparticles with high magnetic moment and well-defined size and shape, being designed to simultaneously fulfill multiple biomedical functionalities, have been thoroughly evaluated. The review summarizes recent results in manufacturing novel magnetic nanoparticle systems, as well as the use of proper characterization methods that are relevant to the magneto-responsive nature, size range, surface chemistry, structuring behavior, and exploitation conditions of magnetic nanosystems. These refer to particle size, size distribution and aggregation characteristics, zeta potential/surface charge, surface coating, functionalization and catalytic activity, morphology (shape, surface area, surface topology, crystallinity), solubility and stability (e.g., solubility in biological fluids, stability on storage), as well as to DC and AC magnetic properties, particle agglomerates formation, and flow behavior under applied magnetic field (magnetorheology).

This paper is an in-depth analysis devoted to two basic types of water based magnetic fluids (MFs), containing magnetite nanoparticles with electrostatic and with electro-steric stabilization, both obtained by chemical coprecipitation synthesis under atmospheric conditions. The two sets of magnetic fluid samples, one with citric acid (MF/CA) and the other with oleic acid (MF/OA) coated magnetic nanoparticles, respectively, achieved saturation magnetization values of 78.20 kA m-1 for the electrostatically and 48.73 kA m-1 for the electro-sterically stabilized aqueous ferrofluids which are among the highest reported to date. A comprehensive comparative analysis combining electron microscopy, X-ray photoelectron spectroscopy, attenuated total reflectance Fourier transform infrared spectroscopy, vibrating sample magnetometry, small-angle X-ray and neutron scattering, dynamic light scattering and magneto-rheometry revealed similarities and essential differences on the microscopic and macroscopic level between the two kinds of water-based ferrofluids. While the saturation magnetization values are quite different, the hydrodynamic volume fractions of the highest concentration MF/CA and MF/OA samples are practically the same, due to the significantly different thicknesses of the particles' coating layers. The results of volume fraction dependent structure analyses over a large concentration range by small-angle X-ray and neutron scattering, correlated with magneto-rheological investigations for the electrostatically stabilized MFs, demonstrate formation of short chains of magnetic nanoparticles which are relatively stable against coagulation with increasing concentration, while for MFs with electro-steric stabilization, magnetic field and shear rate dependent loosely bound structures are observed. These particle structures in MF/OA samples manifest themselves already at low volume fraction values, which can be attributed mainly to magnetic interactions of larger size particles, besides non-magnetic interactions mediated by excess surfactant.

The article presents a rheological model for magnetorheological fluids (MRF) by blending a quasi-newtonian behavior at very low shear stress with a Herschel—Bulkley model for large shear stress value where the suspension displays a shear-thinning behavior. The model parameters allow the identification of a yield point on the flow curve, where the shear stress reaches a local maximum for large magnetic field intensity. It is shown that our model accurately fits the experimental data over a wide range of shear rate and coil electric current intensity values. A main advantage of our model is that it can be used in regular CFD codes to compute the MRF flow in practical applications. We present such a numerical example, and validate the numerical results against a quasi-analytical solution.