Metal-containing intermacromolecular complexes: Electrochemical and viscometric studies in DMF-methanol mixture

Summary Multicomponent intermacromolecular complexes have been prepared from some typical phenolic copolymers with a non-ionic polymer (e.g. PVP), and a polyelectrolyte (e.g. PAA). Some transition metal ions (e.g. Cu(II) and Ni (II)) have been incorporated in the complex through its unreacted co-ordinating groups. The formation of these complexes has been studied by several techniques, such as viscometry, conductometry, potentiometry, IR and UV spectrophotometry. A scheme has been presented to explain the mode of interaction of the various components.     

Thermal expansion characteristics of a titanium modified austenitic stainless steel: measurement by high-temperature X-ray diffraction and modelling using Grüneisen formalism

The thermal expansion of a titanium modified, swelling resistant austenitic stainless steel designated as D9 is studied by measuring the lattice parameter as a function of temperature in the range 300-1300 K by high-temperature X-ray diffraction technique. The thermal expansion data thus obtained is in reasonable agreement with the typical thermal expansion values reported for similar nuclear grade austenitic stainless steels. However, at temperatures exceeding 900 K, the measured thermal expansivity exhibits a pronounced non-linear increase due partly to the precipitation of complex carbide and intermetallic phases. The high-temperature thermal expansion data obtained in the present study are augmented by modelling the low-temperature thermal expansion behaviour by Grüneisen formalism.     

Dynamic bandwidth control of the virtual path in an asynchronoustransfer mode network

The virtual path concept has several valuable features to construct an economical and efficient asynchronous transfer mode (ATM) network. One of them is bandwidth control which affords transmission efficiency improvement through statistical sharing of capacity. An effective bandwidth control algorithm and its calculated performance are described. Network performance with the algorithm is evaluated, and the bandwidth control is shown to successfully improve network transmission efficiency with only a slight increase in processing load compared to the fixed bandwidth scheme. A method is also proposed to equalize call loss probability for each virtual path. The effectiveness of the method is demonstrated by analysis     

Signal processing using cellular neural networks

The cellular neural network (CNN) architecture combines the best features from traditional fully-connected analog neural networks and digital cellular automata. The network can rapidly process continuous-valued (gray-scale) input signals (such as images) and perform many computation functions which traditionally were implemented in digital form. Here, we briefly introduce the the theory of CNN circuits, provide some examples of CNN applications to image processing, and discuss work toward a CNN implementation in custom CMOS VLSI. The role of analog computer-aided design (CAD) will be briefly presented as it relates to analog neural network implementation.This work is supported in part by the Office of Naval Research under Contract N00014-89-J1402, and the National Science Foundation under grant MIP-8912639.     

89-GHz fT room-temperature silicon MOSFETs

The authors report the implementation of deep-submicrometer Si MOSFETs that at room temperature have a unity-current-gain cutoff frequency (f_T) of 89 GHz, for a drain-to-source bias of 1.5 V, a gate-to-source bias of 1 V, a gate oxide thickness of 40 Å, and a channel length of 0.15 μm. The fabrication procedure is mostly conventional, except for the e-beam defined gates. The speed performance is achieved through an intrinsic transit time of only 1.8 ps across the active device region