Networks with hexagonal circuits in co-ordination polymers of metal ions (Zn-II, Cd-II) with 1,1 '-(1,4-butanediyl)bis(imidazole)

Three new compounds, [ZnL1.5(H2O)(SO4)]. 6H(2)O 1, [ZnL1.5(H2O)(2)][NO3](2). 2H(2)O 2 and [CdL1.5(H2O)(2)(SO4)]. 4H(2)O 3 were obtained from self-assembly of the corresponding metal salts with 1,1'-(1,4-butanediyl)bis(imidazole) (L). In both 1 and 2 zinc ion is five-co-ordinated, showing a less-common trigonal bipyramidal co-ordination polyhedron, while cadmium ion of 3 is six-co-ordinated with a common octahedral arrangement. The sulfate ions of 1 and 3 are co-ordinated, however the nitrate ions of 2 are not. Each of the three compounds is composed of a (6, 3) network with the hexagonal smallest circuit containing six metal ions and six L; each L is co-ordinated to two metal ions, acting as a bridging ligand. In 1 the 2-D sheet of (6, 3) networks is interpenetrated in an inclined mode by symmetry related, identical sheets to give an interlocked 3-D structure, while the (6, 3) networks of both 2 and 3 stack in a parallel fashion to construct frameworks having channels.

Fabrication and characterization of active and sequential circuits utilizing Schottky-wrap-gate-controlled GaAs hexagonal nanowire network structures

For realization of hexagonal BDD-based digital systems, active and sequential circuits including inverters, flip flops and ring oscillators are designed and fabricated on GaAs-based hexagonal nanowire networks controlled by Schottky wrap gates (WPGs), and their operations are characterized. Fabricated inverters show comparatively high transfer gain of more than 10. Clear and correct operation of hexagonal set-reset flip flops (SR-FFs) is obtained at room temperature. Fabricated hexagonal D-type flip flop (D-FF) circuits integrating twelve WPG field effect transistors (FETs) show capturing input signal by triggering although the output swing is small. Oscillatory output is successfully obtained in a fabricated 7-stage hexagonal ring oscillator. Obtained results confirm that a good possibility to realize practical digital systems can be implemented by the present circuit approach.

Potential light source for photonic integrated circuits based on the equilateral triangle resonator

The semiconductor microlasers based on the equilateral triangle resonator (ETR) can be fabricated from the edge-emitting laser wafer by dry-etching technique, and the directional emission can be obtained by connecting an output waveguide to one of the vertices of the ETR. We investigate the mode characteristics, especially the mode quality factor, for the ETR with imperfect vertices, which is inevitable in the real technique process. The numerical simulations show that the confined modes can still have a high quality factor in the ETR with imperfect vertices. We can expect that the microlasers is a suitable light source for photonic integrated circuits.

Artificial neural networks expecting more advanced microelectronics technology

　

Parameters Inversion of Fluid-Saturated Porous Media Based on Neural Networks

The multi-layers feedforward neural network is used for inversion of material constants of fluid-saturated porous media. The direct analysis of fluid-saturated porous media is carried out with the boundary element method. The dynamic displacement responses obtained from direct analysis for prescribed material parameters constitute the sample sets training neural network. By virtue of the effective L-M training algorithm and the Tikhonov regularization method as well as the GCV method for an appropriate selection of regularization parameter, the inverse mapping from dynamic displacement responses to material constants is performed. Numerical examples demonstrate the validity of the neural network method.

Pattern Recognition With Weighted Complex Networks

In this paper we introduce a weighted complex networks model to investigate and recognize structures of patterns. The regular treating in pattern recognition models is to describe each pattern as a high-dimensional vector which however is insufficient to express the structural information. Thus, a number of methods are developed to extract the structural information, such as different feature extraction algorithms used in pre-processing steps, or the local receptive fields in convolutional networks. In our model, each pattern is attributed to a weighted complex network, whose topology represents the structure of that pattern. Based upon the training samples, we get several prototypal complex networks which could stand for the general structural characteristics of patterns in different categories. We use these prototypal networks to recognize the unknown patterns. It is an attempt to use complex networks in pattern recognition, and our result shows the potential for real-world pattern recognition. A spatial parameter is introduced to get the optimal recognition accuracy, and it remains constant insensitive to the amount of training samples. We have discussed the interesting properties of the prototypal networks. An approximate linear relation is found between the strength and color of vertexes, in which we could compare the structural difference between each category. We have visualized these prototypal networks to show that their topology indeed represents the common characteristics of patterns. We have also shown that the asymmetric strength distribution in these prototypal networks brings high robustness for recognition. Our study may cast a light on understanding the mechanism of the biologic neuronal systems in object recognition as well.

On the formation of well-aligned ZnO nanowall networks by catalyst-free thermal evaporation method

Two-dimensional ZnO nanowall networks were grown on ZnO-coated silicon by thermal evaporation at low temperature without catalysts or additives. All of the results from scanning electronic spectroscope, X-ray diffraction and Raman scattering confirmed that the ZnO nanowalls were vertically aligned and c-axis oriented. The room-temperature photoluminescence spectra showed a dominated UV peak at 378 nm, and a much suppressed orange emission centered at similar to 590 nm. This demonstrates fairly good crystal quality and optical properties of the product. A possible three-step, zinc vapor-controlled process was proposed to explain the growth of well-aligned ZnO nanowall networks. The pre-coated ZnO template layer plays a key role during the synthesis process, which guides the growth direction of the synthesized products. (C) 2007 Elsevier B.V. All rights reserved.