A Reaction Diffusion Model Of Pattern Formation In Clustering Of Adatoms On Silicon Surfaces

We study a reaction diffusion model which describes the formation of patterns on surfaces having defects. Through this model, the primary goal is to study the growth process of Ge on Si surface. We consider a two species reaction diffusion process where the reacting species are assumed to diffuse on the two dimensional surface with first order interconversion reaction occuring at various defect sites which we call reaction centers. Two models of defects, namely a ring defect and a point defect are considered separately. As reaction centers are assumed to be strongly localized in space, the proposed reaction-diffusion model is found to be exactly solvable. We use Green's function method to study the dynamics of reaction diffusion processes. Further we explore this model through Monte Carlo (MC) simulations to study the growth processes in the presence of a large number of defects. The first passage time statistics has been studied numerically. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. [http://dx.doi.org/10.1063/1.4757592]Microelectronics Research Cente

Probing the Low Mass X-ray Binaries/Globular Cluster connection in NGC1399

We present a wide field study of the Globular Clusters/Low Mass X-ray Binaries connection in the cD elliptical NGC1399, combining HST/ACS and Chandra high resolution data. We find evidence that LMXB formation likelihood is influenced by GCs structural parameters, in addition to the well known effects of mass and metallicity, independently from galactocentric distance.Comment: in press in the Proceedings of the X-ray 2009 Conference, 7-11 September 2009, Bologna, Ital

An Automated Home Made Low Cost Vibrating Sample Magnetometer

The design and operation of a homemade low cost vibrating sample magnetometer is described here. The sensitivity of this instrument is better than 10-2 emu and found to be very efficient for the measurement of magnetization of most of the ferromagnetic and other magnetic materials as a function of temperature down to 77 K and magnetic field upto 800 Oe. Both M(H) and M(T) data acquisition are fully automated employing computer and Labview softwar