MnSi1.7_{1.7} nanoparticles embedded in Si: Superparamagnetism with a collective behavior

The doping of Mn in Si is attracting research attentions due to the possibility to fabricate Si-based diluted magnetic semiconductors. However, the low solubility of Mn in Si favors the precipitation of Mn ions even at non-equilibrium growth conditions. MnSi$_{1.7}$ nanoparticles are the common precipitates, which show exotic magnetic properties in comparison with the MnSi$_{1.7}$ bulk phase. In this paper we present the static and dynamic magnetic properties of MnSi$_{1.7}$ nanoparticles. Using the Preisach model, we derive the magnetic parameters, such as the magnetization of individual particles, the distribution of coercive fields and the inter-particle interaction field. Time-dependent magnetization measurements reveal a spin-glass behavior of the system.Comment: 11 pages, 6 figures, submitted to PR

Improved Magnetic Information Storage using Return-Point Memory

The traditional magnetic storage mechanisms (both analog and digital) apply an external field signal H(t) to a hysteretic magnetic material, and read the remanent magnetization M(t), which is (roughly) proportional to H(t). We propose a new analog method of recovering the signal from the magnetic material, making use of the shape of the hysteresis loop M(H). The field H, ``stored'' in a region with N domains or particles, can be recovered with fluctuations of order 1/N using the new method - much superior to the 1/sqrt{N} fluctuations in traditional analog storage.Comment: 9 pages, 15 figure