No abstract

Aggregates of magnetic nanoparticles (MNPs) exhibit unusual properties due to the interplay of small system size and long-range dipole-dipole interactions. Using the micromagnetic simulation software OOMMF, we study the spin morphologies and heat dissipation in micron-size spherical assemblies of MNPs. In particular, we examine the sensitivity of these properties to the dipolar strength, manipulated by the interparticle separation. As OOMMF is not designed for such a study, we have incorporated a novel scaling protocol for this purpose. We believe that it is essential for all studies where volume fractions are varied. Our main results are as follows: (i) Dense assemblies exhibit strong dipolar effects which yield local magnetic order in the core but not on the surface, where moments are randomly oriented. (ii) The probability distribution of ground-state energy exhibits a long high-energy tail for surface spins in contrast to small tails for the core spins. Consequently, there is a wide variation in the energy of surface spins but not the core spins. (iii) There is strong correlation between ground-state energy and heating properties on application of an oscillating magnetic field h(t) = h o cos 2πf t: the particles in the core heat uniformly, while those on the surface exhibit a wide range from cold to intensely hot. (iv) Specific choices of h o and f yield characteristic spatial heat distributions, e.g., hot surface and cold core, or vice versa. (iv) For all values of h o and f that we consider, heating was maximum at a specific volume fraction. These results are especially relevant in the context of contemporary applications such as hyperthermia and chemotherapy, and also for novel materials such as smart polymer beads and superspin glasses.

PACS 61.30.Dk -Continuum models and theories of liquid crystal structure PACS 61.30.Gd -Orientational order of liquid crystals; electric and magnetic field effects on order PACS 42.79.Kr -Display devices, liquid-crystal devices Abstract -We study a dilute suspension of magnetic nanoparticles in a nematic-filled micron-sized shallow well with tangent boundary conditions. We use a phenomenological approach to study stable textures dictated by the interplay between confinement, boundary effects and nematic coupling with suspended nanoparticles. We numerically compute the stable textures for both the nematic order parameter and the averaged magnetization, as a function of the coupling strength and a new phenomenological parameter. We observe stable domain walls for the magnetization vector and stable vortices in the nematic host, for appropriate choices of the phenomenological parameters, and these stable patterns may have new technological applications.

We study the dynamics of a suspension of magnetic nanoparticles. Their relaxation times are strongly size-dependent. The dominant mode of relaxation is also governed by the size of the particles. As a result the dynamics is greatly altered due to polydispersity in the sample. We study the effect of polydispersity on the response functions. These exhibit significant changes as the parameters characterizing polydispersity are varied. We also provide a procedure to extract the particle size distribution in a polydisperse sample using Cole-Cole plots. Further the presence of attractive interactions causes aggregation of particles leading to the formation of clusters. Repulsive interactions along with thermal disorder not only hinder aggregation, but also introduce the possibility of removal of particles or "fragmentation" from clusters. The competing mechanisms of aggregation and fragmentation yield a distribution of cluster sizes in the steady-state. We attempt to understand the formation of clusters and their distributions using a model incorporating the phenomena of aggregation and fragmentation. Scaling forms for quantities of interest have been obtained. Finally we compare our numerical results with experimental data. These comparisons are satisfactory.

We study the ground-state (T = 0) morphologies in the d = 3 random-field Ising model (RFIM) using a computationally efficient graph-cut method. We focus on paramagnetic states which arise for disorder strengths ∆ > ∆ c , where ∆ c is the critical disorder strength at T = 0. These paramagnetic states consist of correlated "domains" of up and down spins which are separated by rough, fractal interfaces. They show novel scattering properties with a cusp singularity in the correlation function at short distances. PACS numbers: 64.60.De -Statistical mechanics of model systems: Ising model, Monte Carlo techniques, etc.; 68.35.Rh -Phase transitions and critical phenomena; 75.60.Ch -Domain walls and domain structure