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

Phases, many-body entropy measures and coherence of interacting bosons in optical lattices

Already a few bosons with contact interparticle interactions in small optical lattices feature a variety of quantum phases: superfluid, Mott-insulator and fermionized Tonks gases can be probed in such systems. To detect these phases -- pivotal for both experiment and theory -- as well as their many-body properties we analyze several distinct measures for the one-body and many-body Shannon information entropies. We exemplify the connection of these entropies with spatial correlations in the many-body state by contrasting them to the Glauber normalized correlation functions. To obtain the ground-state for lattices with commensurate filling (i.e. an integer number of particles per site) for the full range of repulsive interparticle interactions we utilize the multiconfigurational time-dependent Hartree method for bosons (MCTDHB) in order to solve the many-boson Schr\"odinger equation. We demonstrate that all emergent phases -- the superfluid, the Mott insulator, and the fermionized gas can be characterized equivalently by our many-body entropy measures and by Glauber's normalized correlation functions. In contrast to our many-body entropy measures, single-particle entropy cannot capture these transitions.Comment: 11 pages, 7 figures, software available at http://ultracold.or

Impact of random dopant induced fluctuations on sub-15nm UTB SOI 6T SRAM cells

The CMOS scaling increases the impact of intrinsic parameter fluctuation on the yield and functionality of SRAM. A statistical circuit simulation framework which can fully capture intrinsic parameter fluctuation information into the compact model has been developed. The impact of discrete random dopants in the source and drain regions on 6T SRAM cells has been investigated for well scaled ultra thin body (UTB) SOI MOSFETs with physical channel length in the range of 10nm to 5nm

Kinetic arrest of the first order ferromagnetic to antiferromagnetic transition in Ce(Fe0.96_{0.96}Ru0.04_{0.04})2_2 : formation of a magnetic-glass

We present results of dc magnetization and magnetic relaxation study showing the kinetic arrest of a first order ferromagnetic to antiferromagnetic transition in Ce(Fe$_{0.96}$Ru$_{0.04}$)$_2$. This leads to the formation of a non-ergodic glass-like magnetic state. The onset of the magnetic-glass transformation is tracked through the slowing down of the magnetization dynamics. This glassy state is formed with the assistance of an external magnetic field and this is distinctly different from the well known 'spin-glass' state.Comment: 10 pages of text and 4 figure

The impact of random doping effects on CMOS SRAM cell

The SRAM has a very constrained cell area and is consequently sensitive to the intrinsic parameter fluctuations ubiquitous in decananometer scale MOSFETs. Using a statistical circuit simulation methodology, which can fully collate intrinsic parameter fluctuation information into compact model sets, the impact of random device doping on 6-T SRAM static noise margins, and read and write characteristics are investigated in detail for well-scaled 35 nm physical gate length devices. We conclude that intrinsic parameter fluctuations will become a major limitation to further conventional MOSFET SRAM scaling

UTB SOI SRAM cell stability under the influence of intrinsic parameter fluctuation

Intrinsic parameter fluctuations steadily increases with CMOS technology scaling. Around the 90nm technology node, such fluctuations will eliminate much of the available noise margin in SRAM based on conventional MOSFETs. Ultra thin body (UTB) SOI MOSFETs are expected to replace conventional MOSFETs for integrated memory applications due to superior electrostatic integrity and better resistant to some of the sources of intrinsic parameter fluctuations. To fully realise the performance benefits of UTB SOI based SRAM cells a statistical circuit simulation methodology which can fully capture intrinsic parameter fluctuation information into the compact model is developed. The impact on 6T SRAM static noise margin characteristics of discrete random dopants in the source/drain regions and body-thickness variations has been investigated for well scaled devices with physical channel length in the range of 10nm to 5nm. A comparison with the behaviour of a 6T SRAM based on a conventional 35nm MOSFET is also presented