A Simulation Based Study and Analysis of Double Gate Tunnel FET Performance for Low Stand-By Power Applications

The conventional metal oxide semiconductor field effect transistor (MOSFET)may not be suitable for future low standby power (LSTP) applications due to its high off-state current as the sub-threshold swing is theoretically limited to 60mV/decade. Tunnel field effect transistor (TFET) based on gate controlled band to band tunneling has attracted attention for such applications due to its extremely small sub-threshold swing (much less than 60mV/decade). This paper takes a simulation approach to gain some insight into its electrostatics and the carrier transport mechanism. Using 2D device simulations, a thorough study and analysis of the electrical parameters of the planar double gate TFET is performed. Due to excellent sub-threshold characteristics and a reverse biased structure, it offers orders of magnitude less leakage current compared to the conventional MOSFET. In this work, it is shown that the device can be scaled down to channel lengths as small as 30 nm without affecting its performance. Also, it is observed that the bulk region of the device plays a major role in determining the sub-threshold characteristics of the device and considerable improvement in performance (in terms of ION/IOFF ratio) can be achieved if the thickness of the device is reduced. An ION/IOFF ratio of 2x1012 and a minimum point sub-threshold swing of 22mV/decade is obtained.

Multi-physics self-consistent modeling in nanotechnological applications: quantum dots and quantum-well lasers

This paper reports a self-consistent Poisson-Schr¨odinger scheme including the effects of the piezoelectricity, the spontaneous polarization and the charge density on the electronic states and the quasi-Fermi level energy in wurtzite type semiconductor heterojunction and quantum-laser.

10 Years of Click Chemistry: Synthesis and Applications of Ferrocene-Derived Triazoles

Click chemistry has played a significant role as a rapid and versatile strategy for conjugating two molecular fragments under very mild reaction conditions. Introduction of ferrocene-derived triazole systems using click chemistry has attracted enormous interest in various fields due to its potential applications in electrochemical techniques for detection and sensing. The present discussion focuses on the synthesis of ferrocene-triazole and the importance of using a CuAAC reaction for such conjugation. Applications of ferrocene-based click reactions in conjugate chemistry, asymmetric catalysis, medicinal chemistry, host-guest interactions, and materials chemistry have been highlighted.

Spectral Finite Element Modeling of Complex Structures for Applications in Real-time Structural Health Monitoring

In this paper we discuss the recent progresses in spectral finite element modeling of complex structures and its application in real-time structural health monitoring system based on sensor-actuator network and near real-time computation of Damage Force Indicator (DFI) vector. A waveguide network formalism is developed by mapping the original variational problem into the variational problem involving product spaces of 1D waveguides. Numerical convergence is studied using a h()-refinement scheme, where is the wavelength of interest. Computational issues towards successful implementation of this method with SHM system are discussed.

An Objective Evaluation of Displacement-Amplifying Compliant Mechanisms for Sensor Applications

Displacement-amplifying compliant mechanisms (DaCMs) reported in literature are mostly used for actuator applications. This paper considers them for sensor applications that rely on displacement measurement, and evaluates them objectively. The main goal is to increase the sensitivity under constraints imposed by several secondary requirements and practical constraints. A spring-mass-lever model that effectively captures the addition of a DaCM to a sensor is used in comparing eight DaCMs. We observe that they significantly differ in performance criteria such as geometric advantage, stiffness, natural frequency, mode amplification, factor of safety against failure, cross-axis stiffness, etc., but none excel in all. Thus, a combined figure of merit is proposed using which the most suitable DaCM could be selected for a sensor application. A case-study of a micro machined capacitive accelerometer and another case-study of a vision-based force sensor are included to illustrate the general evaluation and selection procedure of DaCMs with specific applications. Some other insights gained with the analysis presented here were the optimum size-scale for a DaCM, the effect on its natural frequency, limits on its stiffness, and working range of the sensor.

Performance Modeling based on Multidimensional Surface Learning for Performance Predictions of Parallel Applications in Non-Dedicated Environments

Modeling the performance behavior of parallel applications to predict the execution times of the applications for larger problem sizes and number of processors has been an active area of research for several years. The existing curve fitting strategies for performance modeling utilize data from experiments that are conducted under uniform loading conditions. Hence the accuracy of these models degrade when the load conditions on the machines and network change. In this paper, we analyze a curve fitting model that attempts to predict execution times for any load conditions that may exist on the systems during application execution. Based on the experiments conducted with the model for a parallel eigenvalue problem, we propose a multi-dimensional curve-fitting model based on rational polynomials for performance predictions of parallel applications in non-dedicated environments. We used the rational polynomial based model to predict execution times for 2 other parallel applications on systems with large load dynamics. In all the cases, the model gave good predictions of execution times with average percentage prediction errors of less than 20%