Magnetic nanoparticles: surface effects and properties related to biomedicine applications

Abstract

Due to finite size effects, such as the high surface-to-volume ratio and different crystal structures, magnetic nanoparticles are found to exhibit interesting and considerably different magnetic properties than those found in their corresponding bulk materials. These nanoparticles can be synthesized in several ways (e.g., chemical and physical) with controllable sizes enabling their comparison to biological organisms from cells (10-100 μm), viruses, genes, down to proteins (3-50 nm). The optimization of the nanoparticles' size, size distribution, agglomeration, coating, and shapes along with their unique magnetic properties prompted the application of nanoparticles of this type in diverse fields. Biomedicine is one of these fields where intensive research is currently being conducted. In this review, we will discuss the magnetic properties of nanoparticles which are directly related to their applications in biomedicine. We will focus mainly on surface effects and ferrite nanoparticles, and on one diagnostic application of magnetic nanoparticles as magnetic resonance imaging contrast agents.

Figure 1

The spinel structure of ferrites is shown indicating the tetrahedral and octahedral sites. This figure is copied from the following website http://www.tf.uni-kiel.de/matwis/amat/def_en/kap_2/basics/b2_1_6.html.

Figure 2

SEM of well dispersed spherical nanoparticles suspended on agarose gel.

Figure 3

TEM of nanoparticles showing moderate clustering of particles. Size definition becomes more difficult due to agglomeration.

Figure 4

Severe degree of agglomeration of nanoparticles that renders definition of particle morphology and size very difficult. Quantitative analysis in MRI relies on measurement of nanoparticle size and magnetic moment.

Figure 5

Different concentrations (mM per kg gel) of uncoated Mn_0.5Zn_0.5Gd_0.02Fe_1.98O₃ nanoparticles suspended in agarose gel contained in glass tubes surrounded by a water bath [185].

Figure 6

Spin-echo images at 1.5T at different echo times and temperatures. The images show larger signal decay due to higher nanoparticles concentrations, longer echoes, and lower temperatures. In order to understand the signal weighting by T1 and T2 relaxation times, quantitative measurement of many nanoparticle-specific parameters are needed such as particle size and the degree of agglomeration. Any possible variation of these parameters (and the magnetic moment) with temperature must also be taken into account.

Figure 7

Linear relationship between the relaxation rates and nanoparticle concentration is demonstrated. The slope of the curves defines relaxivity.

Figure 8

Magnetization curves for Gd-substituted MnZn-ferrite nanoparticles where saturation is not achieved even at very large applied field. Two superparamagnetic and one paramagnetic component are required for good fitting. These extra components can be explained in terms of isolated spins or dead phases (see text).