Finite element analysis of electromagnetic scattering from a cavity

A finite element method (FEM) is implemented to compute the radar cross section of a two-dimensional (2D) cavity embedded in an infinite ground plane. The method is based on the variational formulation which uses the Fourier transform to couple the fields outside the cavity and those inside the cavity; hence, the scattering problem can be reduced to a bounded domain. The convergence of the discrete finite element problem is analyzed. Numerical results are presented and compared with those obtained by the standard finite element-Green function method and by the 2D integral equation method.     

Second harmonic generation from a ferroelectric film

We derive an expression for transmittivity (T_SHG) of second harmonic generation (SHG) signals from a ferroelectric (FE) film. Intensities of up and down fields in the medium are investigated in relation to T_SHG. The derivations are made based on undepletion of input fields and nonlinear wave equation derived from the Maxwell equations. We present two cases: film without mirrors and with partial mirrors. Expressions for the newly derived nonlinear susceptibility coefficients of SHG for real crystal symmetry [J. Opt. Soc. Am. B 19 (2002) 2007] are used to get more realistic results. Variations in T_SHG with respect to film thickness are illustrated.     

1/f noise in large-area Hg<Subscript>1−x</Subscript>Cd<Subscript>x</Subscript>Te photodiodes

The 1/f noise in photovoltaic (PV) molecular-beam epitaxy (MBE)-grown Hg_1−xCd_xTe double-layer planar heterostructure (DLPH) large-area detectors is a critical noise component with the potential to limit sensitivity of the cross-track infrared sounder (CrIS) instrument. Therefore, an understanding of the origins and mechanisms of noise currents in these PV detectors is of great importance. Excess low-frequency noise has been measured on a number of 1000-μm-diameter active-area detectors of varying “quality” (i.e., having a wide range of I-V characteristics at 78 K). The 1/f noise was measured as a function of cut-off wavelength under illuminated conditions. For short-wave infrared (SWIR) detectors at 98 K, minimal 1/f noise was measured when the total current was dominated by diffusion with white noise spectral density in the mid-10⁻¹⁵A/Hz^1/2 range. For SWIR detectors dominated by other than diffusion current, the ratio, α, of the noise current in unit bandwidth i_n(f = 1 Hz, V_d = −60 mV, and Δf = 1 Hz) to dark current I_d(V_d = −60 mV) was α_SW-d = i_n/I_d ∼ 1 × 10⁻³. The SWIR detectors measured at 0 mV under illuminated conditions had median α_SW-P = i_n/I_ph ∼ 7 × 10⁻⁶. For mid-wave infrared (MWIR) detectors, α_MW-d = i_n/I_d ∼ 2 × 10⁻⁴, due to tunneling current contributions to the 1/f noise. Measurements on forty-nine 1000-μm-diameter MWIR detectors under illuminated conditions at 98 K and −60 mV bias resulted in α_MW-P = i_n/I_ph = 4.16 ± 1.69 × 10⁻⁶. A significant point to note is that the photo-induced noise spectra are nearly identical at 0 mV and 100 mV reverse bias, with a noise-current-to-photocurrent ratio, α_MW-P, in the mid 10⁻⁶ range. For long-wave infrared (LWIR) detectors measured at 78 K, the ratio, α_LW-d = i_n/I_d ∼ 6 × 10⁻⁶, for the best performers. The majority of the LWIR detectors exhibited α_LW-d on the order of 2 × 10⁻⁵. The photo-induced 1/f noise had α_LW-P = i_n/I_ph ∼ 5 × 10⁻⁶. The value of the noise-current-to-dark-current ratio, α appears to increase with increasing bandgap. It is not clear if this is due to different current mechanisms impacting 1/f noise performance. Measurements on detectors of different bandgaps are needed at temperatures where diffusion current is the dominant current. Excess low-frequency noise measurements made as a function of detector reverse bias indicate 1/f noise may result primarily from the dominant current mechanism at each particular bias. The 1/f noise was not a direct function of the applied bias.     

Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.     

Synthesis of ZSM‐5 Films and Monoliths with Bimodal Micro/Mesoscopic Structures

A route to synthesize ZSM‐5 crystals with a bimodal micro/mesoscopic pore system has been developed in this study; the successful incorporation of the mesopores within the ZSM‐5 structure was performed using tetrapropylammonium hydroxide (TPAOH)‐impregnated mesoporous materials containing carbon nanotubes in the pores, which were encapsulated in the ZSM‐5 crystals during a solid rearrangement process within the framework. Such mesoporous ZSM‐5 zeolites can be readily obtained as powders, thin films, or monoliths.     

The First Template‐Free Growth of Crystalline Silicon Microtubes

A simple template‐free high‐temperature evaporation method was developed for the growth of crystalline Si microtubes for the first time. As‐grown Si microtubes were characterized using X‐ray diffraction, scanning electron microscopy, transmission electron microscopy, and room‐temperature photoluminescence. The lengths of the Si tubes can reach several hundreds of micrometers; some of them have lengths on the order of millimeters. Each tube has a uniform outer diameter along its entire length, and the typical outer diameter is ≈ 2–3 μm. Most of the tubes have a wall thickness of ≈ 400–500 nm, though a considerable number of them exhibit a very thin wall thickness of ≈ 50 nm. Room‐temperature photoluminescence measurement shows the as‐synthesized Si microtubes have two strong emission peaks centered at ≈ 589 nm and ≈ 617 nm and a weak emission peak centered at ≈ 455 nm. A possible mechanism for the formation of these Si tubes is proposed. We believe that the present discovery of the crystalline Si microtubes will promote further experimental studies on their physical properties and smart applications.     

Securing Mobile Ad hoc Networks — A Motivational Approach

Mobile ad hoc networks rely on the co-operation of devices that route for each other. This immediately presents security problems. Each device's data passes through the not so friendly hands of other devices. Forwarding devices must use their processing power and battery power to route packets for others. When bandwidth is limited they must also use bandwidth that they might want to use for themselves. These are not great issues with the first incarnations of ad hoc networks — military systems or others where all the devices are owned by a single organisation. However, if ad hoc networks are to be generally deployed and become an alternative or adjunct to future cellular systems, then ways to encourage co-operation are required. This revised version was published online in July 2006 with corrections to the Cover Date.     

Mining constrained gradients in large databases

Many data analysis tasks can be viewed as search or mining in a multidimensional space (MDS). In such MDSs, dimensions capture potentially important factors for given applications, and cells represent combinations of values for the factors. To systematically analyze data in MDS, an interesting notion, called "cubegrade" was recently introduced by Imielinski et al. [2002], which focuses on the notable changes in measures in MDS by comparing a cell (which we refer to as probe cell) with its gradient cells, namely, its ancestors, descendants, and siblings. We call such queries gradient analysis queries (GQs). Since an MDS can contain billions of cells, it is important to answer GQs efficiently. We focus on developing efficient methods for mining GQs constrained by certain (weakly) antimonotone constraints. Instead of conducting an independent gradient-cell search once per probe cell, which is inefficient due to much repeated work, we propose an efficient algorithm, LiveSet-Driven. This algorithm finds all good gradient-probe cell pairs in one search pass. It utilizes measure-value analysis and dimension-match analysis in a set-oriented manner, to achieve bidirectional pruning between the sets of hopeful probe cells and of hopeful gradient cells. Moreover, it adopts a hypertree structure and an H-cubing method to compress data and to maximize sharing of computation. Our performance study shows that this algorithm is efficient and scalable. In addition to data cubes, we extend our study to another important scenario: mining constrained gradients in transactional databases where each item is associated with some measures such as price. Such transactional databases can be viewed as sparse MDSs where items represent dimensions, although they have significantly different characteristics than data cubes. We outline efficient mining methods for this problem.     

Scaling planar silicon devices

The generation-over-generation scaling of critical CMOS technology parameters is ultimately bound by nonscalable limitations, such as the thermal voltage and the elementary electronic charge. Sustained improvement in performance and density has required the introduction of new device structures and materials. Partially depleted SOI, a most recent MOSFET innovation, has extended VLSI performance while introducing unique idiosyncrasies. Fully depleted SOI is one logical extension of this device design direction. Gate dielectric tunneling, device self-heating, and single-event upsets present developers of these next-generation devices with new challenges. Strained silicon and high-permittivity gate dielectric are examples of new materials that will enable CMOS developers to continue to deliver device performance enhancements in the sub-100 nm regime.     

Effects of SiN passivation and high-electric field on AlGaN-GaN HFET degradation

The authors report on the effects of silicon nitride (SiN) surface passivation and high-electric field stress (hot electron stress) on the degradation of undoped AlGaN-GaN power HFETs. Stressed devices demonstrated a decrease in the drain current and maximum transconductance and an increase in the parasitic drain series resistance, gate leakage, and subthreshold current. The unpassivated devices showed more significant degradation than SiN passivated devices. Gate lag phenomenon was observed from unpassivated devices and removed by SiN passivation. However, SiN passivated devices also showed gate lag phenomena after high-electric field stress, which suggests possible changes in surface trap profiles occurred during high-electric field stress test.