Gate and drain currents in off-state buried-type p-channel LDDMOSFETs

The buried-type p-channel LDD MOSFETs biased at high positive gate voltage exhibit novel characteristics: (1) the ratio of the drain to gate currents is about 1×10^-3 to 5×10^-3; and (2) the gate and drain currents both are functions of only the gate voltage minus the n-well bias. Such characteristics are addressed based on the formation of the surface n ⁺ inversion layer due to the punchthrough of the buried channel to the underlying shallow p-n junction. The measured gate current is due to the Fowler-Nordheim tunneling of electrons from this inversion layer surface and the holes generated within the high-field oxide constitute the drain current. The n⁺ inversion layer surface potential is found to be equal to the n-well bias plus 0.55 V. As a result, both the oxide field and the gate and drain currents are independent of drain voltage     

Production and properties of micro‐porous glas bubble zinc and aluminium composites

Micro‐porous syntactic foams were produced by means of integration of glass bubbles into aluminium and zinc matrices. Preforms of glass bubbles were pressure infiltrated with the alloys AlSi9Cu9 ans ZnAl4Cu using squeeze casting. The preforms were sintered thermically without the use of bonding agents. Using the combination of different sintering steps syntactic foams with locally different densities could be produced. The mechanical properties of the foams were tested indicating a high compression strength of the foams and a very good compression energy absorption. Furthermore, corrosion behaviour and behaviour at higher temperatures were investigated.     

From information to probability: An axiomatic approach—Inference is information processing

We define the very rich language of composed conditionals on a three‐valued logic and use this language as the communication tool between man and machine. Communication takes place for three reasons: knowledge acquisition, query, and response. Learning, thinking, and answering questions are of a pure information theoretical nature. The pivot of this knowledge processing concept is the amount of information (bit) we receive if a conditional becomes true. We follow an axiomatic approach to information theory rather than the classical probabilistic approach of Shannon; information comes first, and then comes probability. In the light of this philosophy, query and response experience new interpretations. Both, acquisition and response are realized by maximizing entropy and minimizing relative entropy, respectively. The iterative solution of these mathematical optimization problems gives new insights into the adaptation of prior knowledge to new information. Our expert system shell SPIRIT supports this kind of knowledge processing, which will be established by suitable examples. © 2003 Wiley Periodicals, Inc.     

Prediction of fire classification for wood based products. A multivariate statistical approach based on the cone calorimeter

Wood has long traditions as a building material, and is often used in construction elements, and as interior and exterior surfaces in the Nordic countries. In most applications, there are reaction to fire requirements to products used as surfaces, e.g. in escape routes and larger public spaces. Most wood products will therefore have to be treated with fire retardant (FR) agents to fulfil the strict requirements to properties connected to heat release and flame spread. Unfortunately, FR agents usually also increase the smoke production, as they cause a more incomplete combustion of the wood. The wood product manufacturers seek to find the optimal amount of FR additives where both heat release and smoke production in the classifying test are within the requirements given in the building regulations. This paper describes models for prediction of the European reaction to fire classes of wood products. The models are based on multivariate statistical analysis, and use test results from the cone calorimeter test as input. The presented models are, with very good precision, able to predict which Euroclass and additional smoke class a wood based product would obtain if it were to be tested in the single burning item test. Copyright © 2006 John Wiley & Sons, Ltd.     

On-line learning delivery decision support system for highlyproduct mixed semiconductor foundry

A production learning system (PLS) based on the tool model was constructed as a decision support and real-time information update system to forecast the cycle time. A tool model includes a waiting model and a processing model. Each of the waiting and processing models uses a backpropagation neural network to establish the relationship between the input and output (time) of the model. Hence, cycle time estimation, tool group move and confirm line item performance (CLIP) value can be obtained based on the memory stored in the neural network. The result shows that the forecasting ability of the PLS has an error rate below 8% on average     

Efficient design/simulation algorithms for simultaneous switching noise in leadframe packages

 Two new modeling and simulation approaches for Simultaneous Switching Noise (SSN) are described and compared to “brute force” simulation by SPICE. Both simulation accuracy and simulation run-time are considered. The two new approaches are: 1) the “effective inductance” method, in which an approximate, very efficient method of extracting an SSN L _eff  is utilized; and 2) the “macromodel” method, in which the complex inductance network responsible for SSN is represented by only a few dominant poles in the frequency domain and the time domain response is obtained by an efficient convolution algorithm. Both approaches are shown to be accurate and fast, but only the effective inductance algorithm is robust in numerical convergence. Received: 19 March 1997 / Accepted: 25 March 1997     

Adaptive predictive control algorithm based on Laguerre Functional Model

Laguerre Functional Model has many advantages such as good approximation capability for the variances of system time‐delay, order and other structural parameters, low computational complexity, and the facility of online parameter identification, etc., so this model is suitable for complex industrial process control. A series of successful applications have been gained in linear and non‐linear predictive control fields by the control algorithm based on Laguerre Functional Model, however, former researchers have not systemically brought forward the theoretical analyses of the stability, robustness, and steady‐state performance of this algorithm, which are the keys to guarantee the feasibility of the control algorithm fundamentally. Aimed at this problem, we introduce the principles of the Incremental Mode Linear Laguerre Predictive Control (IMLLPC) algorithm, and then systemically propose the theoretical analyses and proofs of the stability and robustness of the algorithm, in addition, we also put forward the steady‐state performance analysis. At last, the control performances of this algorithm on two different physical industrial plants are presented in detail, and a number of experimental results validate the feasibility and superiority of IMLLPC algorithm. Copyright © 2005 John Wiley & Sons, Ltd.     

The dominance of the K I-field for a crack under stress wave loading

The extent of the dominant singular field is investigated for a finite crack under stress wave loading. Using a boundary integral equation method the complete solution as well as the near field solution is determined. A comparison of the two fields indicates that the singular field dominates within a small domain at the crack tip. The size of the dominance region in the dynamic case may be very different from that in the static case.     

Comparisons of PWM and one-cycle control for power amplifier with multilevel converter

Based on the concepts of cascade multilevel converters and one-cycle technique, comparisons are conducted to characterize the distortion of the pulsewidth modulation (PWM) and one-cycle control methods that were applied to converters. Simulation results for the different control schemes are obtained in PSIM software initially to see the effect of one-cycle control different from that of PWM control. Through the comparisons, the advantages and disadvantages are identified for each method. The one-cycle scheme is better than PWM control in reducing undesirable harmonics and tracing dynamic waveforms. Simulation and experimental results are also provided to verify the conclusions.