Metal-free growth of Si/SiO2 nanowires by annealing SiOx (x < 2) films deposited by PECVD

A new metal catalysis-free method of fabricating Si or SiO2 nanowires (NWs) compatible with Si CMOS technology was proposed by annealing SiOx (x < 2) films deposited by plasma -enhanced chemical vapor deposition (PECVD). The effects of the Si content (x value) and thickness of SiOx films, the annealing process and flowing gas ambient on the NW growth were studied in detail. The results indicated that the SiOx film of a thickness below 300 rim with x value close to 1 was most favorable for NW growth upon annealing at 1000-1150 degrees C in the flowing gas mixture of N-2 and H-2. NWs of 50-100nm in diameter and tens of micrometers in length were synthesized by this method. The formation mechanism was likely to be related to a new type of oxide assisted growth (OAG) mechanism, with Si nanoclusters in SiOx films after phase separation serving as the nuclei for the growth of NWs in SiOx films > 200nm, and SiO molecules from thin SiO, film decomposition inducing the NW growth in films < 100nm. An effective preliminary method to control NW growth direction was also demonstrated by etching trenches in SiOx films followed by annealing.

A Novel Geometric Algorithm for Blind Image Restoration Based on High-Dimensional Space

A novel geometric algorithm for blind image restoration is proposed in this paper, based on High-Dimensional Space Geometrical Informatics (HDSGI) theory. In this algorithm every image is considered as a point, and the location relationship of the points in high-dimensional space, i.e. the intrinsic relationship of images is analyzed. Then geometric technique of "blurring-blurring-deblurring" is adopted to get the deblurring images. Comparing with other existing algorithms like Wiener filter, super resolution image restoration etc., the experimental results show that the proposed algorithm could not only obtain better details of images but also reduces the computational complexity with less computing time. The novel algorithm probably shows a new direction for blind image restoration with promising perspective of applications.

Effects of annealing treatment on the formation of CO2 in ZnO thin films grown by metal-organic chemical vapor deposition

Post-growth annealing was carried out on ZnO thin films grown by metal-organic chemical vapor deposition (MOCVD). The grain size of ZnO thin film increases monotonically with annealing temperature. The ZnO thin films were preferential to c-axis oriented after annealing as confirmed by Xray diffraction (XRD) measurements. Fourier transformation infrared transmission measurements showed that ZnO films grown at low temperature contains CO2 molecules after post-growth annealing. A two-step reaction process has been proposed to explain the formation mechanism of CO2, which indicates the possible chemical reaction processes during the metal-organic chemical vapor deposition of ZnO films.

Photoluminescence spectroscopy and positron annihilation spectroscopy probe of alloying and annealing effects in nonpolar m-plane ZnMgO thin films

Temperature-dependent photoluminescence characteristics of non-polar m-plane ZnO and ZnMgO alloy films grown by metal organic chemical vapor deposition have been studied. The enhancement in emission intensity caused by localized excitons in m-plane ZnMgO alloy films was directly observed and it can be further improved after annealing in nitrogen. The concentration of Zn vacancies in the films was increased by alloying with Mg, which was detected by positron annihilation spectroscopy. This result is very important to directly explain why undoped Zn1-xMgxO thin films can show p-type conduction by controlling Mg content, as discussed by Li [Appl. Phys. Lett. 91, 232115 (2007)].

An Enhanced Particle Swarm Optimization Algorithm

Particle Swarm Optimization (PSO) algorithm is often used for finding optimal solution, but it easily entraps into the local extremum in later evolution period. Based on improved chaos searching strategy, an enhanced particle swarm optimization algorithm is proposed in this study. When particles get into the local extremum, they are activated by chaos search strategy, where the chaos search area is controlled in the neighborhood of current optimal solution by reducing search area of variables. The new algorithm not only gets rid of the local extremum effectively but also enhances the precision of convergence significantly. Experiment results show that the proposed algorithm is better than standard PSO algorithm in both precision and stability.

A shortest path algorithm for moving objects in spatial network databases

One of the most important kinds of queries in Spatial Network Databases (SNDB) to support location-based services (LBS) is the shortest path query. Given an object in a network, e.g. a location of a car on a road network, and a set of objects of interests, e.g. hotels,gas station, and car, the shortest path query returns the shortest path from the query object to interested objects. The studies of shortest path query have two kinds of ways, online processing and preprocessing. The studies of preprocessing suppose that the interest objects are static. This paper proposes a shortest path algorithm with a set of index structures to support the situation of moving objects. This algorithm can transform a dynamic problem to a static problem. In this paper we focus on road networks. However, our algorithms do not use any domain specific information, and therefore can be applied to any network. This algorithm’s complexity is O(klog2 i), and traditional Dijkstra’s complexity is O((i + k)2).

a shortest path algorithm for moving objects in spatial network databases

中国计算机学会