Dipolar-coupled moment correlations in clusters of magnetic nanoparticles

Here, we investigate the nature of the moment coupling between 10-nm DMSA-coated magnetic nanoparticles, in both colloidal dispersion and in powder form. The individual iron oxide cores were composed of > 95% maghemite and agglomerated to clusters. At room temperature the ensemble behaved as a superparamagnet according to M\"ossbauer and magnetization measurements, however, with clear signs of dipolar interactions at low temperatures. Analysis of temperature-dependent AC susceptibility data in the superparamagnetic regime indicates a tendency for dipolar coupled anticorrelations of the core moments within the clusters. To resolve the directional correlations between the particle moments we performed polarized small-angle neutron scattering and determined the magnetic spin-flip cross-section of the powder in low magnetic field at 300 K. We extract the underlying pair distance distribution function of the magnetization vector field by an indirect Fourier transform of the cross-section, and which suggests positive as well as negative correlations between nearest neighbor moments, with anticorrelations clearly dominating for next-nearest moments. These tendencies are confirmed by Monte Carlo simulations of such core-clusters.Comment: 11 pages, 6 figure

Field-dependent dynamic responses from dilute magnetic nanoparticle dispersions

The response of magnetic nanoparticles (MNPs) to an oscillating magnetic field outside the linear response region is important for several applications including magnetic hyperthermia, magnetic resonance imaging and biodetection. The size and magnetic moment are two critical parameters for the performance of a colloidal MNP dispersion. We present and demonstrate the use of optomagnetic (OM) and AC susceptibility (ACS) measurements vs. frequency and magnetic field strength to obtain the size and magnetic moment distributions including the correlation between the distributions. The correlation between the size and the magnetic moment contains information on the morphology and intrinsic structure of the particle. In OM measurements, the variation of the second harmonic light transmission through a dispersion of MNPs is measured in response to an oscillating magnetic field. We solve the Fokker-Planck equations for MNPs with a permanent magnetic moment, and develop analytical approximations to the ACS and the OM signals that also account for the change in the curve shapes with increasing field strength. Further, we describe the influence of induced magnetic moments on the signals, by solving the Fokker-Planck equation for particles, which apart from the permanent magnetic moment may also have an induced magnetic moment and shape anisotropy. Using the results from the Fokker-Planck calculations we fit ACS and OM measurements on two multi-core particle systems. The obtained fit parameters also describe the correlations between the magnetic moment and size of the particles. From such an analysis on a commercially available polydisperse multicore particle system with an average particle size of 80 nm, we find that the MNP magnetic moment is proportional to the square root of the hydrodynamic size

Field-dependent dynamic responses from dilute magnetic nanoparticle dispersions

The response of magnetic nanoparticles (MNPs) to an oscillating magnetic field outside the linear response region is important for several applications including magnetic hyperthermia, magnetic resonance imaging and biodetection. The size and magnetic moment are two critical parameters for the performance of a colloidal MNP dispersion. We present and demonstrate the use of optomagnetic (OM) and AC susceptibility (ACS) measurements vs. frequency and magnetic field strength to obtain the size and magnetic moment distributions including the correlation between the distributions. The correlation between the size and the magnetic moment contains information on the morphology and intrinsic structure of the particle. In OM measurements, the variation of the second harmonic light transmission through a dispersion of MNPs is measured in response to an oscillating magnetic field. We solve the Fokker-Planck equations for MNPs with a permanent magnetic moment, and develop analytical approximations to the ACS and the OM signals that also account for the change in the curve shapes with increasing field strength. Further, we describe the influence of induced magnetic moments on the signals, by solving the Fokker-Planck equation for particles, which apart from the permanent magnetic moment may also have an induced magnetic moment and shape anisotropy. Using the results from the Fokker-Planck calculations we fit ACS and OM measurements on two multi-core particle systems. The obtained fit parameters also describe the correlations between the magnetic moment and size of the particles. From such an analysis on a commercially available polydisperse multicore particle system with an average particle size of 80 nm, we find that the MNP magnetic moment is proportional to the square root of the hydrodynamic size

Robust approaches for model‐free small‐angle scattering data analysis

The small‐angle neutron scattering data of nanostructured magnetic samples contain information regarding their chemical and magnetic properties. Often, the first step to access characteristic magnetic and structural length scales is a model‐free investigation. However, due to measurement uncertainties and a restricted q range, a direct Fourier transform usually fails and results in ambiguous distributions. To circumvent these problems, different methods have been introduced to derive regularized, more stable correlation functions, with the indirect Fourier transform being the most prominent approach. Here, the indirect Fourier transform is compared with the singular value decomposition and an iterative algorithm. These approaches are used to determine the correlation function from magnetic small‐angle neutron scattering data of a powder sample of iron oxide nanoparticles; it is shown that with all three methods, in principle, the same correlation function can be derived. Each method has certain advantages and disadvantages, and thus the recommendation is to combine these three approaches to obtain robust results.Three different approaches are compared for determination of the correlation function from the small‐angle neutron scattering data of a powder sample of iron oxide nanoparticles

Robust approaches for model-free small-angle scattering data analysis

The small-angle neutron scattering data of nanostructured magnetic samples contain information regarding their chemical and magnetic properties. Often, the first step to access characteristic magnetic and structural length scales is a model-free investigation. However, due to measurement uncertainties and a restricted q range, a direct Fourier transform usually fails and results in ambiguous distributions. To circumvent these problems, different methods have been introduced to derive regularized, more stable correlation functions, with the indirect Fourier transform being the most prominent approach. Here, the indirect Fourier transform is compared with the singular value decomposition and an iterative algorithm. These approaches are used to determine the correlation function from magnetic small-angle neutron scattering data of a powder sample of iron oxide nanoparticles; it is shown that with all three methods, in principle, the same correlation function can be derived. Each method has certain advantages and disadvantages, and thus the recommendation is to combine these three approaches to obtain robust results

Thermodynamic Charge-to-Mass Sensor for Colloids, Proteins, and Polyelectrolytes

A sensor is introduced that gauges the ratio of charge z to mass m of macro-ions in liquid media. The conductivity is measured in a small volume of salt solution, separated from the macro-ions by a semipermeable membrane. The mobile counterions released by the macro-ions increase the measured salt concentration, from which z/m can be calculated without any adjustable parameter. The charge sensor constitutes a noninvasive method that probes unperturbed macro-ions in a manner that is independent of (the distribution in) macro-ion size and shape. We validate the sensor’s general applicability for three kinds of macro-ions, spanning 2 orders of magnitude in z/m, namely, dextran sulfate, bovine serum albumin, and colloidal silica. Measured z/m values comply for all macro-ion types with independent information on macro-ion surface charge

Size analysis of single-core magnetic nanoparticles

Single-core iron-oxide nanoparticles with nominal core diameters of 14\ua0nm and 19\ua0nm were analyzed with a variety of non-magnetic and magnetic analysis techniques, including transmission electron microscopy (TEM), dynamic light scattering (DLS), static magnetization vs. magnetic field (M-H) measurements, ac susceptibility (ACS) and magnetorelaxometry (MRX). From the experimental data, distributions of core and hydrodynamic sizes are derived. Except for TEM where a number-weighted distribution is directly obtained, models have to be applied in order to determine size distributions from the measurand. It was found that the mean core diameters determined from TEM, M-H, ACS and MRX measurements agree well although they are based on different models (Langevin function, Brownian and N\ue9el relaxation times). Especially for the sample with large cores, particle interaction effects come into play, causing agglomerates which were detected in DLS, ACS and MRX measurements. We observed that the number and size of agglomerates can be minimized by sufficiently strong diluting the suspension

Ultrasmall Iron Oxide Nanoparticles for Biomedical Applications: Improving the Colloidal and Magnetic Properties

A considerable increase in the saturation magnetization, <i>M</i>_s (40%), and initial susceptibility of ultrasmall (<5 nm) iron oxide nanoparticles prepared by laser pyrolysis was obtained through an optimized acid treatment. Moreover, a significant enhancement in the colloidal properties, such as smaller aggregate sizes in aqueous media and increased surface charge densities, was found after this chemical protocol. The results are consistent with a reduction in nanoparticle surface disorder induced by a dissolution–recrystallization mechanism