Synthesis and magnetic characterization of nickel ferrite nanoparticles prepared by co-precipitation route

Magnetic nanoparticles of nickel ferrite (NiFe2O4) have been synthesized by co-precipitation route using stable ferric and nickel salts with sodium hydroxide as the precipitating agent and oleic acid as the surfactant. X-ray diffraction (XRD) and transmission electron microscope (TEM) analyses confirmed the formation of single-phase nickel ferrite nanoparticles in the range 8-28 nm depending upon the annealing temperature of the samples during the synthesis. The size of the particles (d) was observed to be increasing linearly with annealing temperature of the sample while the coercivity with particle size goes through a maximum, peaking at similar to 11 nm and then decreases for larger particles. Typical blocking effects were observed below similar to 225 K for all the prepared samples. The superparamagnetic blocking temperature (T-B) was found to be increasing with increasing particle size that has been attributed to the increased effective anisotropy energy of the nanoparticles. The saturation moment of all the samples was found much below the bulk value of nickel ferrite that has been attributed to the disordered surface spins or dead/inert layer in these nanoparticles. (c) 2008 Elsevier B. V. All rights reserved.

Magnetic characterization of Co1-xNixFe2O4 (0 <= x <= 1) nanoparticles prepared by co-precipitation route

Magnetic nanoparticles of Ni-doped cobalt ferrite [Co1-xNixFe2O4(0 <= x <= 1)] synthesized by coprecipitation route have been studied as a function of doping concentration (x) and particle size. The size of the particles as determined by X-ray diffractometer (XRD) and transmission electron microscope (TEM) analyses was found in the range 12-48 nm. The coercivity (H-C) and saturation magnetization (M-S) showed a decreasing behavior with increasing Ni concentration. M-S of all the samples annealed at 600 degrees C lies in the range 65.8-13.7 emu/gm. Field-cooled (FC) studies of the samples showed horizontal shift (exchange bias) and vertical shift in the magnetization loop. Strong decrease in exchange bias (H-b) and vertical shift (delta M) was found for low Ni concentrations while negligible decrease was found at higher concentrations. The presence of exchange bias in the low Ni-concentration region has been explained with reference to the interface spins interaction between a surface region (with structural and spin disorder) and a ferrimagnetic core region. M(T) graphs of the samples showed a decreasing trend of blocking temperature (T-b) with increasing Ni concentration. The decrease of T-b with increasing Ni concentration has been attributed to the lower anisotropy energy of Ni+2 ions as compared to Co+2 that increases the probability of the jump across the anisotropy barrier which in turn decreases the blocking temperature of the system.

Application of probabilistic neural network in the clinical diagnosis of cancers based on clinical chemistry data

As a recently developed and powerful classification tool, probabilistic neural network was used to distinguish cancer patients from healthy persons according to the levels of nucleosides in human urine. Two datasets (containing 32 and 50 patterns, respectively) were investigated and the total consistency rate obtained was 100% for dataset 1 and 94% for dataset 2. To evaluate the performance of probabilistic neural network, linear discriminant analysis and learning vector quantization network, were also applied to the classification problem. The results showed that the predictive ability of the probabilistic neural network is stronger than the others in this study. Moreover, the recognition rate for dataset 2 can achieve to 100% if combining, these three methods together, which indicated the promising potential of clinical diagnosis by combining different methods. (C) 2002 Elsevier Science B.V. All rights reserved.