Optimisation of spacer layer thickness in n-AlxGa1?xAs/p+-GaAs heterojunction diodes grown by molecular beam epitaxy

The effect of an undoped GaAs spacer layer at the heterojunction interface of MBE-grown n-AlxGa1?xAs/p+-GaAs diodes has been investigated by electroluminescence, dynamic secondary ion mass spectrometry and current/voltage measurements. A consistent picture emerges of the role of the spacer layer in accommodating beryllium migration. A simple procedure to optimise the spacer layer thickness is suggested.     

High-gain, V-band, low-noise MMIC amplifiers usingpseudomorphic MODFETs

State-of-the-art, 60-GHz, low-noise MMICs based on pseudomorphic modulation-doped FETs, with 0.25-μm×60-μm gates offset 0.3 μm from the source ohmic, are discussed. Single-state low-noise amplifiers (LNAs) exhibited minimum noise figures of 2.90 dB with 4.1 dB of associated gain at 59.25 GHz. Dual-state MMICs had minimum noise figures of 3.5 dB and 10.8 dB of associated gain at 58.50 GHz. Cascaded four-stage LNAs (two dual-stage MMICs) had minimum noise figures of 3.7 dB and over 20.7 dB of associated gain at 58.0 GHz. Finally, when biased for maximum gain, the four-stage amplifier exhibited over 30.4 dB of gain at 60.0 GHz     

Automating the modeling and optimization of the performance ofsignal transforms

Fast implementations of discrete signal transforms, such as the discrete Fourier transform (DFT), the Walsh-Hadamard transform (WHT), and the discrete trigonometric transforms (DTTs), can be viewed as factorizations of their corresponding transformation matrices. A given signal transform can have many different factorizations, with each factorization represented by a unique but mathematically equivalent formula. When implemented in code, these formulas can have significantly different running times on the same processor, sometimes differing by an order of magnitude. Further, the optimal implementations on various processors are often different. Given this complexity, a crucial problem is automating the modeling and optimization of the performance of signal transform implementations. To enable computer modeling of signal processing performance, we have developed and analyzed more than 15 feature sets to describe formulas representing specific transforms. Using some of these features and a limited set of training data, we have successfully trained neural networks to learn to accurately predict performance of formulas with error rates less than 5%. In the direction of optimization, we have developed a new stochastic evolutionary algorithm known as STEER that finds fast implementations of a variety of signal transforms. STEER is able to optimize completely new transforms specified by a user. We present results that show that STEER can find discrete cosine transform formulas that are 10-20% faster than what a dynamic programming search finds     

Characterization of PV array output using a small number of measured parameters

The purpose of the present study was to develop a sufficiently good fit for the measured I–V curve of a PV module and array using only three easily measurable parameters: —the open-circuit voltage (V_oc); —the short-circuit current (I_sc); —the maximum power (P_m). With an additional three parameters ( ; ; ) it is possible to describe any I–V curve, taking into account cell temperature T and solar radiation Q. This method has been tested on various solar array panels as well as on a single 10 cm dia. solar cell. The difference between the real curve and the proposed fit was found to be less than 3 percent for a fixed temperature and radiation and about 6 percent for various combinations of temperature and radiation.     

Comparison of trihalomethanes in tap water and blood

Trihalomethane (THM) concentrations in blood and tap water were measured for 50 women living in two locations with different bromide concentrations and disinfectant types. Blood samples were taken from each woman early in the morning prior to any major water-use activity and again immediately after showering. Each residence was sampled for THMs in tap water prior to the woman's shower. Cobb County, GA, tap water exhibited high THM concentrations composed primarily of chloroform. Corpus Christi, TX, tap water exhibited lower THM concentrations with significant proportions of brominated THMs. THMs in tap water and blood were compared using mole fraction speciation, extent of bromine incorporation, and correlation analysis. Results indicated that THMs in the blood rose significantly as a result of showering, that showering shifted the THM distribution in the blood toward that found in the corresponding tap water, and that THMs measured in the blood of women living in the two locations reflected species and concentration differences in their respective tap waters. In general, blood concentrations were not significantly correlated with tap water concentrations. This finding suggests that other factors, in addition to tap water concentrations, may be important in determining THM concentrations in the blood.     

A 3-V 340-mW 14-b 75-Msample/s CMOS ADC with 85-dB SFDR at Nyquistinput

This paper describes the design of a 14-b 75-Msample/s pipeline analog-to-digital converter (ADC) implemented in a 0.35-μm double-poly triple-metal CMOS process. The ADC uses a 4-b first stage to relax capacitor-matching requirements, buffered bootstrapping to reduce signal-dependent charge injection, and a flip-around track-and-hold amplifier with wide common-mode compliance to reduce noise and power consumption. It achieves 14-b accuracy without calibration or dithering. Typical differential nonlinearity is 0.6 LSB, and integral nonlinearity is 2 LSB. The ADC also achieves 73-dB signal-to-noise ratio, and 85-dB spurious-free dynamic range over the first Nyquist band. The 7.8-mm² ADC operates with a 2.7- to 3.6-V supply, and dissipates 340 mW at 3 V