The Path to a Porous Semiconductor Multilayer

Thin films are the basis of much of recent technological advance, ranging from coatings with mechanical or optical benefits to platforms for nanoscale electronics. In the latter, semiconductors have been the norm ever since silicon became the main construction material for a multitude of electronical components. The array of characteristics of silicon-based systems can be widened by manipulating the structure of the thin films at the nanoscale - for instance, by making them porous. The different characteristics of different films can then to some extent be combined by simple superposition. Thin films can be manufactured using many different methods. One emerging field is cluster beam deposition, where aggregates of hundreds or thousands of atoms are deposited one by one to form a layer, the characteristics of which depend on the parameters of deposition. One critical parameter is deposition energy, which dictates how porous, if at all, the layer becomes. Other parameters, such as sputtering rate and aggregation conditions, have an effect on the size and consistency of the individual clusters. Understanding nanoscale processes, which cannot be observed experimentally, is fundamental to optimizing experimental techniques and inventing new possibilities for advances at this scale. Atomistic computer simulations offer a window to the world of nanometers and nanoseconds in a way unparalleled by the most accurate of microscopes. Transmission electron microscope image simulations can then bridge this gap by providing a tangible link between the simulated and the experimental. In this thesis, the entire process of cluster beam deposition is explored using molecular dynamics and image simulations. The process begins with the formation of the clusters, which is investigated for Si/Ge in an Ar atmosphere. The structure of the clusters is optimized to bring it as close to the experimental ideal as possible. Then, clusters are deposited, one by one, onto a substrate, until a sufficiently thick layer has been produced. Finally, the concept is expanded by further deposition with different parameters, resulting in multiple superimposed layers of different porosities. This work demonstrates how the aggregation of clusters is not entirely understood within the scope of the approximations used in the simulations; yet, it is also shown how the continued deposition of clusters with a varying deposition energy can lead to a novel kind of nanostructured thin film: a multielemental porous multilayer. According to theory, these new structures have characteristics that can be tailored for a variety of applications, with precision heretofore unseen in conventional multilayer manufacture.

Structural Studies Of Analgesics And Their Interactions .1. Crystal And Molecular-Structure Of Antipyrine

The complex crystallizes in the space group P21/c with four formula units in a unit cell of dimensionsa= 12.747, b= 7.416, c= 17.894 A and/3= 90.2 °. The structure has been solved by the symbolic addition procedure using three dimensional photographic data and refined to an R value of 0.079 for 2019 observed reflexions. The pyramidal nature of the two hetero nitrogen atoms in the antipyrine molecule is inter:nediate between that observed in free antipyrine and in some of its metal complexes. The molecule is more polar than that in crystals of free antipyrine but less so compared with that in metal complexes. In the salicylic acid molecule, the hydroxyl group forms an internal hydrogen bond with one of the oxygen atoms in the carboxyl group. The association between the salicylic acid and the antipyrine molecules is achieved through an intermolecular hydrogen bond with the other carboxyl oxygen atom in the salicylic acid molecule as the proton donor and the carboxyl oxygen atom of the antipyrine molecule as the acceptor

HFinFET: A Scalable, High Performance, Low Leakage Hybrid n-Channel FET

In this letter, we propose the design and simulation study of a novel transistor, called HFinFET, which is a hybrid of an HEMT and a FinFET, to obtain excellent performance and good OFF-state control. Followed by the description of the design, 3-D device simulation has been performed to predict the characteristics of the device. The device has been benchmarked against published state of the art HEMT as well as planar and nonplanar Si n-MOSFET data of comparable gate length using standard benchmarking techniques.

Lightning-Induced Current and Voltage on a Rocket in the Presence of Its Trailing Exhaust Plume

This paper presents time-domain characteristics of induced current and voltage on a rocket in the presence of its exhaust plume when an electromagnetic (EM) wave generated by a nearby lightning discharge is incident on it. For the EM-field interaction with the rocket, the finite-difference time-domain technique has been used. The distributed electrical parameters, such as capacitance and inductance of the rocket and its exhaust plume, are computed using the method of moments technique. For the electrical characterization of the exhaust plume, the computational fluid dynamics technique has been used. The computed peak value of the electrical conductivity of the exhaust plume is 0.12 S/m near the exit plane and it reduces to 0.02 S/m at the downstream end. The relative permittivity varies from 0.91 to 0.99. The exhaust plume behaves as a good conductor for EM fields with frequencies less than 2.285 GHz. It has been observed that the peak value of the induced current on the rocket gets enhanced significantly in the presence of the conducting exhaust plume for the rocket and exhaust plume dimensions and parameters studied. The magnitude of the time-varying induced current at the tail is much more than that of any other section of the rocket.

Lightning-Induced Current and Voltage on a Rocket in the Presence of Its Trailing Exhaust Plume

This paper presents time-domain characteristics of induced current and voltage on a rocket in the presence of its exhaust plume when an electromagnetic (EM) wave generated by a nearby lightning discharge is incident on it. For the EM-field interaction with the rocket, the finite-difference time-domain technique has been used. The distributed electrical parameters, such as capacitance and inductance of the rocket and its exhaust plume, are computed using the method of moments technique. For the electrical characterization of the exhaust plume, the computational fluid dynamics technique has been used. The computed peak value of the electrical conductivity of the exhaust plume is 0.12 S/m near the exit plane and it reduces to 0.02 S/m at the downstream end. The relative permittivity varies from 0.91 to 0.99. The exhaust plume behaves as a good conductor for EM fields with frequencies less than 2.285 GHz. It has been observed that the peak value of the induced current on the rocket gets enhanced significantly in the presence of the conducting exhaust plume for the rocket and exhaust plume dimensions and parameters studied. The magnitude of the time-varying induced current at the tail is much more than that of any other section of the rocket.

A Survey on Cascaded Multilevel Inverters

Cascaded multilevel inverters synthesize a medium-voltage output based on a series connection of power cells which use standard low-voltage component configurations. This characteristic allows one to achieve high-quality output voltages and input currents and also outstanding availability due to their intrinsic component redundancy. Due to these features, the cascaded multilevel inverter has been recognized as an important alternative in the medium-voltage inverter market. This paper presents a survey of different topologies, control strategies and modulation techniques used by these inverters. Regenerative and advanced topologies are also discussed. Applications where the mentioned features play a key role are shown. Finally, future developments are addressed.

Worst inputs and a bound on the highest peak statistics of a class of non-linear systems

A method is developed by which the input leading to the highest possible response in an interval of time can be determined for a class of non-linear systems. The input, if deterministic, is constrained to have a known finite energy (or norm) in the interval under consideration. In the case of random inputs, the energy is constrained to have a known probability distribution function. The approach has applications when a system has to be put to maximum advantage by getting the largest possible output or when a system has to be designed to the highest maximum response with only the input energy or the energy distribution known. The method is also useful in arriving at a bound on the highest peak distribution of the response, when the excitation is a known random process.As an illustration the Duffing oscillator has been analysed and some numerical results have also been presented.

A Wavelet based Teager Energy Operator for Spike Detection in Microelectrode Array Recordings

Spike detection in neural recordings is the initial step in the creation of brain machine interfaces. The Teager energy operator (TEO) treats a spike as an increase in the `local' energy and detects this increase. The performance of TEO in detecting action potential spikes suffers due to its sensitivity to the frequency of spikes in the presence of noise which is present in microelectrode array (MEA) recordings. The multiresolution TEO (mTEO) method overcomes this shortcoming of the TEO by tuning the parameter k to an optimal value m so as to match to frequency of the spike. In this paper, we present an algorithm for the mTEO using the multiresolution structure of wavelets along with inbuilt lowpass filtering of the subband signals. The algorithm is efficient and can be implemented for real-time processing of neural signals for spike detection. The performance of the algorithm is tested on a simulated neural signal with 10 spike templates obtained from [14]. The background noise is modeled as a colored Gaussian random process. Using the noise standard deviation and autocorrelation functions obtained from recorded data, background noise was simulated by an autoregressive (AR(5)) filter. The simulations show a spike detection accuracy of 90%and above with less than 5% false positives at an SNR of 2.35 dB as compared to 80% accuracy and 10% false positives reported [6] on simulated neural signals.

Helical FDK Algorithms With No Backprojection Weight

In this paper, we present two new filtered backprojection (FBP) type algorithms for cylindrical detector helical cone-beam geometry with no position dependent backprojection weight. The algorithms are extension of the recent exact Hilbert filtering based 2D divergent beam reconstruction with no backprojection weight to the FDK type algorithm for reconstruction in 3D helical trajectory cone-beam tomography. The two algorithms named HFDK-W1 and HFDK-W2 result in better image quality, noise uniformity, lower noise and reduced cone-beam artifacts.

MMSE Receiver for Multiuser Interference Cancellation in Uplink OFDMA

In uplink orthogonal frequency division multiple access (OFDMA) systems, multiuser interference (MUI) occurs due to different carrier frequency offsets (CFO) of different users at the receiver. In this paper, we present a minimum mean square error (MMSE) based approach to MUI cancellation in uplink OFDMA. We derive a recursion to approach the MMSE solution. We present a structure-wise and performance-wise comparison of this recursive MMSE solution with a linear PIC receiver as well as other detectors recently proposed in the literature. We show that the proposed recursive MMSE solution encompasses several known detectors in the literature as special cases.

Estimation of signals in colored non gaussian noise based on Gaussian Mixture models

Non-Gaussianity of signals/noise often results in significant performance degradation for systems, which are designed using the Gaussian assumption. So non-Gaussian signals/noise require a different modelling and processing approach. In this paper, we discuss a new Bayesian estimation technique for non-Gaussian signals corrupted by colored non Gaussian noise. The method is based on using zero mean finite Gaussian Mixture Models (GMMs) for signal and noise. The estimation is done using an adaptive non-causal nonlinear filtering technique. The method involves deriving an estimator in terms of the GMM parameters, which are in turn estimated using the EM algorithm. The proposed filter is of finite length and offers computational feasibility. The simulations show that the proposed method gives a significant improvement compared to the linear filter for a wide variety of noise conditions, including impulsive noise. We also claim that the estimation of signal using the correlation with past and future samples leads to reduced mean squared error as compared to signal estimation based on past samples only.

Wavelet transform based error concealment approach for image denoising

Denoising of images in compressed wavelet domain has potential application in transmission technology such as mobile communication. In this paper, we present a new image denoising scheme based on restoration of bit-planes of wavelet coefficients in compressed domain. It exploits the fundamental property of wavelet transform - its ability to analyze the image at different resolution levels and the edge information associated with each band. The proposed scheme relies on the fact that noise commonly manifests itself as a fine-grained structure in image and wavelet transform allows the restoration strategy to adapt itself according to directional features of edges. The proposed approach shows promising results when compared with conventional unrestored scheme, in context of error reduction and has capability to adapt to situations where noise level in the image varies. The applicability of the proposed approach has implications in restoration of images due to noisy channels. This scheme, in addition, to being very flexible, tries to retain all the features, including edges of the image. The proposed scheme is computationally efficient.

Image reconstruction by inhomogeneous diffusion for positron emission tomography

In positron emission tomography (PET), image reconstruction is a demanding problem. Since, PET image reconstruction is an ill-posed inverse problem, new methodologies need to be developed. Although previous studies show that incorporation of spatial and median priors improves the image quality, the image artifacts such as over-smoothing and streaking are evident in the reconstructed image. In this work, we use a simple, yet powerful technique to tackle the PET image reconstruction problem. Proposed technique is based on the integration of Bayesian approach with that of finite impulse response (FIR) filter. A FIR filter is designed whose coefficients are determined based on the surface diffusion model. The resulting reconstructed image is iteratively filtered and fed back to obtain the new estimate. Experiments are performed on a simulated PET system. The results show that the proposed approach is better than recently proposed MRP algorithm in terms of image quality and normalized mean square error.