Room temperature magnetic quantum cellular automata

All computers process information electronically. A processing method based on magnetism is reported here, in which networks of interacting submicrometer magnetic dots are used to perform logic operations and propagate information at room temperature. The logic states are signaled by the magnetization direction of the single-domain magnetic dots; the dots couple to their nearest neighbors through magnetostatic interactions. Magnetic solitons carry information through the networks, and an applied oscillating magnetic field feeds energy into the system and serves as a clock. These networks offer a several thousandfold increase in integration density and a hundredfold reduction in power dissipation over current microelectronic technology.

The effect of carbon encapsulation on the magnetic properties of Ni nanoparticles produced by arc discharge in de-ionized water

Despite intensive research on optimizing the methods for depositing carbon encapsulated ferromagnetic nanoparticles, the effect of the carbon cages remains unclear. In the present work, the effect of the graphitic cages on the magnetization of the ferromagnetic core has been studied by comparing the magnetic properties of pure and carbon encapsulated Ni particles of the same size. The carbon encapsulated Ni particles were formed using an electric arc discharge in de-ionized water between a solid graphite cathode and an anode consisting of Ni and C in a mass ratio of Ni:C = 7:3. This method is shown to have potential for low cost production of carbon encapsulated Ni nanoparticle samples with narrow particle size distributions. X-ray diffraction (XRD) and high resolution transmission electron microscopy (HRTEM) analysis were used to study the crystallography, morphology, and size distribution of the encapsulated and pure Ni nanoparticle samples. The availability of encapsulated particles with various sizes allowed us to elucidate the role of carbon cages in size-dependent properties. Our data suggest that even though encapsulation is beneficial for protection against hostile chemical environments and for avoiding low proximity phenomena, it suppresses the saturation magnetization of the Ni cores.

Multi-channel signal separation

The separation of independent sources from mixed observed data is a fundamental and challenging problem. In many practical situations, observations may be modelled as linear mixtures of a number of source signals, i.e. a linear multi-input multi-output system. A typical example is speech recordings made in an acoustic environment in the presence of background noise and/or competing speakers. Other examples include EEG signals, passive sonar applications and cross-talk in data communications. In this paper, we propose iterative algorithms to solve the n × n linear time invariant system under two different constraints. Some existing solutions for 2 × 2 systems are reviewed and compared.

Bayesian separation and recovery of convolutively mixed autoregressive sources

In this paper we address the problem of the separation and recovery of convolutively mixed autoregressive processes in a Bayesian framework. Solving this problem requires the ability to solve integration and/or optimization problems of complicated posterior distributions. We thus propose efficient stochastic algorithms based on Markov chain Monte Carlo (MCMC) methods. We present three algorithms. The first one is a classical Gibbs sampler that generates samples from the posterior distribution. The two other algorithms are stochastic optimization algorithms that allow to optimize either the marginal distribution of the sources, or the marginal distribution of the parameters of the sources and mixing filters, conditional upon the observation. Simulations are presented.

Resonant Raman characterisation of ultra-thin nano-protective carbon layers for magnetic storage devices

Carbon thin films are very important as protective coatings for a wide range of applications such as magnetic storage devices. The key parameter of interest is the sp3 fraction, since it controls the mechanical properties of the film. Visible Raman spectroscopy is a very popular technique to determine the carbon bonding. However, the visible Raman spectra mainly depend on the configuration and clustering of the sp2 sites. This can result in the Raman spectra of different samples looking similar albeit having a different structure. Thus, visible Raman alone cannot be used to derive the sp3 content. Here we monitor the carbon bonding by using a combined study of Raman spectra taken at two wavelengths (514 and 244 nm). We show how the G peak dispersion is a very useful parameter to investigate the carbon samples and we endorse it as a production-line characterisation tool. The dispersion is proportional to the degree of disorder, thus making it possible to distinguish between graphitic and diamond-like carbon. © 2003 Elsevier B.V. All rights reserved.

Mechanical and magnetic properties of metal fibre networks, with and without a polymeric matrix

Bonded networks of metal fibres are highly porous, permeable materials, which often exhibit relatively high strength. Material of this type has been produced, using melt-extracted ferritic stainless steel fibres, and characterised in terms of fibre volume fraction, fibre segment (joint-to-joint) length and fibre orientation distribution. Young's moduli and yield stresses have been measured. The behaviour when subjected to a magnetic field has also been investigated. This causes macroscopic straining, as the individual fibres become magnetised and tend to align with the applied field. The modeling approach of Markaki and Clyne, recently developed for prediction of the mechanical and magneto-mechanical properties of such materials, is briefly summarised and comparisons are made with experimental data. The effects of filling the inter-fibre void with compliant (polymeric) matrices have also been explored. In general the modeling approach gives reliable predictions, particularly when the network architecture has been characterised using X-ray tomography. © 2005 Published by Elsevier Ltd.

Effect of thickness on the magnetic properties of melt-processed YBCO thick films

The magnetic properties of melt-processed YBa2Cu3O7-δ thick films have been measured and correlated with features in the microstructure at 4.2 and 77 K for film thicknesses between 50 and 140 μm. A qualitative model for the volume magnetization of the films at 4.2 K is proposed in terms of the individual contributions from intra H-S grain, inter H-S grain and granular Jc components.