An 18-mW 2.5-GHz/900-MHz BiCMOS dual frequency synthesizer with<10-Hz RF carrier resolution

A 2.5-GHz/900-MHz dual fractional-N/integer-N frequency synthesizer is implemented in 0.35-μm 25-GHz BiCMOS. A ΔΣ fractional-N synthesizer is employed for RF channels to have agile switching, low in-band noise, and fine frequency resolution. Implementing two synthesizers with an on-chip ΔΣ modulator in a small package is challenging since the modulator induces substantial digital noise. In this work, several design aspects regarding noise coupling are considered. The fractional-N synthesizer offers less than 10-Hz frequency resolution having the in-band noise contribution of -88 dBc/Hz for 2.47-GHz output frequency and -98 dBc/Hz for 1.15-GHz output frequency, both measured at 20-kHz offset frequency. The prototype dual synthesizer consumes 18 mW with 2.6-V supply     

Low-loss high power RF switching using multifinger AlGaN/GaN MOSHFETs

We demonstrate a novel RF switch based on a multifinger AlGaN/GaN MOSHFET. Record high saturation current and breakdown voltage, extremely low gate leakage current and low gate capacitance of the III-N MOSHFETs make them excellent active elements for RF switching. Using a single element test circuit with 1-mm wide multifinger MOSHFET we achieved 0.27 dB insertion loss and more than 40 dB isolation. These parameters can be further improved by impedance matching and by using submicron gate devices. The maximum switching power extrapolated from the results for 1A/mm 100 /spl mu/m wide device exceeds 40 W for a 1-mm wide 2-A/mm MOSHFET.     

Compact WLAN disc antennas

A novel conical beam patch antenna design, suitable for local area network applications, uses a central cylindrical connection from the disc to ground to achieve a large reduction in resonant size. Results on efficiency, bandwidth, and pattern are reported for several prototypes.     

Accurate surface potential determination in Schottky diodes by use of correlated current and capacitance voltage measurements. Application to n–InP

Based on current voltage (I-V_g) and capacitance voltage (C-V_g) measurements, a reliable procedure is proposed to determine the effective surface potential V_d.V_g/ in Schottky diodes. In the framework of thermionic emission, our analysis includes both the effect of the series resistance and the ideality factor, even voltage dependent. This technique is applied to n-type indium phosphide (n-InP) Schottky diodes with and without an interfacial layer and allows us to provide an interpretation of the observed peak on the C-V_g measurements. The study clearly shows that the depletion width and the flat band barrier height deduced from C-V_g, which are important parameters directly related to the surface potential in the semiconductor, should be estimated within our approach to obtain more reliable information.     

13C CP/MAS NMR Spectroscopy of Native and Acid Modified Starches

¹³CP/MAS NMR spectroscopic studies of some starches from cereals (wheat, maize and finger millet), pulses (green gram, chick pea), tuber (potato) and root (tapioca), and their respective acid (HCI, HNO₃) modified starches were carried out. While cereal starches exhibited a triplet signal for their anomeric carbons, pulse, tuber and root starches showed doublets. Line width changes in signals indicated that debranching in the above modified starches led to narrowing of C₆ signals (more pronounced in the case of potato and tapioca starches) and were consistent with the release of branching strains. Potato starch, both native and modified, was found to be different from other starches as inferred from the chemical shift values for their anomeric carbons and line shape. The dihedral angle (ϕ′2) calculated from chemical shift values for C₁ and conformation of dihedral angel (x) as predicted from chemical shift of C₆ are discussed with respect to structural organization.     

Synthesis of artificial neural networks by transconductors only

Hardware implementation of artificial neural networks has been attracting great attention recently. In this work, the analog VLSI implementation of artificial neural networks by using only transconductors is presented. The signal flow graph approach is used in synthesis. The neural flow graph is defined. Synthesis of various neural network configurations by means of neural flow graph is described. The approach presented in this work is technology independent. This approach can be applied to new neural network topologies to be proposed or used with transconductors designed in future technologies.     

Current distribution, resistance, and inductance forsuperconducting strip transmission lines

A method for the calculation of the current distribution, resistance, and inductance matrices for a system of coupled superconducting transmission lines having finite rectangular cross-section is presented. These calculations allow accurate characterization of both high-T_c and low-T _c superconducting strip transmission lines. For a single stripline geometry with finite ground planes, the current distribution, resistance, inductance, and kinetic inductance are calculated as functions of the penetration depth for various film thicknesses. These calculations are then used to determine the penetration depth for Nb, NbN, and YBa₂Cu₃O_7-x superconducting thin films from the measured temperature dependence of the resonant frequency of a stripline resonator. The calculations are also used to convert measured temperature dependence of the quality factor to the intrinsic surface resistance as a function of temperature for an Nb stripline resonator     

Two-stage thermocatalytic upgrading of fuel oil to olefins and fuels over a nanoporous hierarchical acidic catalyst

A two-stage thermocatalytic upgrading process using a novel catalyst was investigated to produce light olefins and liquid fuels from fuel oil. The upgraded oil from the first thermal stage demonstrated lower viscosity and higher crackability compared to the virgin feedstock. In the next step, the vapor-phase catalytic cracking of the upgraded fraction was implemented over a novel nanoporous composite catalyst, characterized by the XRD, FTIR, NH₃- TPD, and N₂ physisorption techniques. In total, more than 55?wt% of light olefins, particularly propylene (25.5?wt%) together with 25.4?wt% and 32.5?wt% of gasoline and diesel fuel were obtained in this process.     

Development of a novel ANFIS-GA method for investigation of effect of inhibitors on asphaltene precipitation

Asphaltene precipitation and deposition in different parts of petroleum industry increase considerably cost and problems in oil production. Due to these facts controlling asphaltene precipitation becomes one of valuable topics for research in petroleum engineering. Utilization of Asphaltene inhibitors is known as one of the dominant methods for controlling asphaltene precipitation so in this paper Adaptive neuro-fuzzy inference system (ANFIS) is joint with Genetic Algorithm (GA) to study effectiveness of asphaltene inhibitors on precipitation in terms of oil and inhibitors properties. In order to prepare and evaluate the ANFIS-GA algorithm, some reliable experimental data were gathered. The obtained results from the comparison shows the coefficient of determination (R²) for training and testing phases are 0.98804 and 0.9916 respectively. The determined indexes and graphical comparisons expresses that ANFIS-GA has enough accuracy and potential to estimate effectiveness of inhibitors on asphaltene precipitation reductions.