The dynamic response analysis of a pyroelectric thin-film infraredsensor with thermal isolation improvement structure

Both theoretical and experimental studies of the substrate effect on the thermal behavior of a PbTiO₃ infrared (IR) sensor have been reported. With active cantilever dimensions of 200×100×5 μm³ formed by etching processes, the pyroelectric micro-electro-mechanical system (pyro/MEMS) structure exhibits a much superior performance to that of a traditional IR-sensing bulk structure under the 800-μW incident optical light with wavelength of 970 nm. Two-order improvement in current responsivity is obtained for the pyro/MEMS structure. This shows the substrate effect on the performance of a pyro/MEMS IR sensor is very significant. A simple model has also been proposed to illustrate the substrate effect more comprehensively     

Effect of fluorinated silicate glass passivation layer on electrical characteristics and dielectric reliabilities for the HfO2/SiON gate stacked nMOSFET

The superior characteristics of the fluorinated hafnium oxide/oxynitride (HfO₂/SiON) gate dielectric are investigated comprehensively. Fluorine is incorporated into the gate dielectric through fluorinated silicate glass (FSG) passivation layer to form fluorinated HfO₂/SiON dielectric. Fluorine incorporation has been proven to eliminate both bulk and interface trap densities due to Hf-F and Si-F bonds formation, which can strongly reduce trap generation as well as trap-assisted tunneling during subsequently constant voltage stress, and results in improved electrical characteristics and dielectric reliabilities. The results clearly indicate that the fluorinated HfO₂/SiON gate dielectric using FSG passivation layer becomes a feasible technology for future ultrathin gate dielectrics applications.     

Ag and Cu migration phenomena on wire-bonding

After storing a plastic packaged sample at 250°C for 588 h, the Au plus 1% Pd wire composition was found to be changed. The Ag and Cu atoms can migrate from the wedge bond through the wire surface and arrive at the ball bond. At the same time, Ag and Cu atoms diffuse into the gold wire itself and form a layer type structure. The atom migration phenomena are due to three driving forces: diffusion, alloy formation, and Galvanic effect. The obtained diffusion rate constant is in the order of 10⁻¹² cm square per sec, which corresponds to an activation energy of 0.7∼0.76 eV. The phases sequence formed by diffusion is inconsistent with the equilibrium Ag-Au-Cu phase diagram which indicates that the present diffusion layer has reached thermodynamic equilibrium.     

Analysis of passively Q-switched lasers with simultaneous modelocking

Simultaneous Q-switching and modelocking in a diode-pumped Nd:YAG/Cr⁴⁺:YAG laser is experimentally demonstrated. A general recurrence is derived for the analysis of the temporal shape of a single Q-switched envelope with mode locked pulse trains. With the developed model, the modelocked pulse energy and the total Q-switched pulse energy can be calculated. Excellent agreement was found between the present results and detailed theoretical computations     

Adaptive parallel interference cancellation for CDMA systems—A weight selection and filtering scheme

Parallel interference cancellation (PIC) is a well-known multiuser detection algorithm in direct-sequence code-division multiple-access (DS-CDMA) systems. It is typically implemented with a multi-stage architecture. One problem associated with the PIC is that unreliable interference cancellation may occur in the early stages and the system performance may be degraded. Thus, the partial PIC detector was developed to control the cancellation level by use of interference cancellation factors. Partial PIC can be implemented with an adaptive form, in which optimal weights are derived using the least mean square (LMS) algorithm. In this paper, we propose an algorithm improving the conventional adaptive partial PIC. The main idea is to reduce the number of active weights in the LMS algorithm, and to perform weight post-filtering such that the resultant excess mean square error can be reduced. We also analyze the performance of the proposed algorithm and derive the bit error rate of the second stage output. Simulation results verify that the proposed algorithm outperforms the conventional partial PIC, and derived analytical results are accurate.     

Artificial neural networks and statistical modeling for electronic stress prediction using thermal profiling

Electronic components are constantly under stress due to factors such as signal density, temperature, humidity, and high current and voltage. Relatively little research has emphasized stress-level prediction under voltage stress. The purpose of this paper was to develop an electronic thermal profile model for stress-level prediction utilizing neural network (NN) and statistical approaches, such as multivariate regression models. Electronic components were removed from boards, subjected to different levels of stress, then replaced. An infrared camera was then used to capture information about component temperature changes over time under normal operating and stress conditions. Statistical analysis of the captured images suggests a strong correlation between thermal profiles and voltage stress levels. Artificial neural network (ANN) and statistical approaches were used to model temperature change profiles for components that had been stressed at different levels, and their predictive ability was compared. Separate data sets were used for model development and model verification. ANN prediction rates were around 70%, compared to 30% for the statistical approach. Experiments were also conducted to evaluate the robustness of the ANN model to the presence of noise in the data. Results suggested that the ANN model was able to accommodate the presence of noise. Various backpropagation (BP) learning algorithms were also evaluated and yielded similar average error rates. A 3-2-1 ANN topology performed better than 3-3-1 or 3-2-2-1 topologies, perhaps because the 3-2-1 topology has a higher data sample to nodes ratio than the other topologies.     

A fast tag identification anti‐collision algorithm for RFID systems

In this work, we propose a highly efficient binary tree‐based anti‐collision algorithm for radio frequency identification (RFID) tag identification. The proposed binary splitting modified dynamic tree (BS‐MDT) algorithm employs a binary splitting tree to achieve accurate tag estimation and a modified dynamic tree algorithm for rapid tag identification. We mathematically evaluate the performance of the BS‐MDT algorithm in terms of the system efficiency and the time system efficiency based on the ISO/IEC 18000‐6 Type B standard. The derived mathematical model is validated using computer simulations. Numerical results show that the proposed BS‐MDT algorithm can provide the system efficiency of 46% and time system efficiency of 74%, outperforming all other well‐performed algorithms.     

Development of a microelectromechanical system pressure sensor for rehabilitation engineering applications

Based on computer finite-element analysis ANSYS 5.3 and microelectromechanical systems (MEMS) technologies, a micropressure sensor was designed and fabricated. The sensor can be used to measure the distribution of normal stress between soft tissues on an above-knee amputee's skin and the contacting surface of a rehabilitation device. A square membrane with dimensions 2400 µm × 2400 µm × 80 µm is formed by backside photolithography and wet etching of an n-type ?100? monolithic silicon wafer. On the middle of the membrane edge, an X-shaped silicon wafer was implanted with boron ions and then enhanced by diffusion to form a piezoresistive strain gauge. In the design process, a finite-element method is used to analyse the effects of pressure sensitivity and its temperature coefficients. The developed micropressure sensors, which have smaller weight and volume than a conventional machine type, perform well and fit our design specifications.     

Current gain dependence on subcollector and etch-stop doping inInGaP/GaAs HBTs

The DC current gain dependence of InGaP/GaAs heterojunction bipolar transistors (HBTs) on subcollector and etch-stop doping is examined. Samples of InGaP/GaAs HBTs having various combinations of subcollector doping and etch-stop doping are grown, and large area 60 μm×60 (μ) HBTs are then fabricated for DC characterization. It is found that the DC current gain has a strong dependence on the doping concentration in the subcollector and the subcollector etch-stop. Maximum gain is achieved when the subcollector is doped at 6~7×10 ¹⁸ cm^-3 while the subcollector etch-stop is doped either above 6×10¹⁸ cm^-3 (current gain/sheet resistance ratio, β/R_b=0.435 at I_c=1 mA) or below 3.5×10¹⁷ cm^-3 (β/R_b=0.426~0.438 at I_c=1 mA). The data show that it is not necessary to heavily dope the subcollector etch-stop to reduce the conduction barrier and to obtain high current gain. The high current gain obtained with the low InGaP etch-stop doping concentration is attributed to the reduction of the effective energy barrier thickness due to band bending at the heterojunction between the InGaP etch-stop and the GaAs subcollector. These results show that the β/R_b of InGaP/GaAs HBTs can improve as much as 69% with the optimized doping concentration in subcollector and subcollector etch-stop     

Maximum contrast beamformer for electromagnetic mapping of brain activity

Beamforming technique can be applied to map the neuronal activities from magnetoencephalographic/electroencephalographic (MEG/EEG) recordings. One of the major difficulties of the scalar-type MEG/EEG beamformer is the determination of accurate dipole orientation, which is essential to an effective spatial filter. This paper presents a new beamforming technique which exploits a maximum contrast criterion to maximize the ratio of the neuronal activity estimated in a specified active state to the activity estimated in a control state. This criterion leads to a closed-form solution of the dipole orientation. Experiments with simulation, phantom, and finger-lifting data clearly demonstrate the effectiveness, efficiency, and accuracy of the proposed method.