K(2)O(2): The most stable oxide of K

We have analyzed the stability of various oxides of K and find that K(2)O(2) is the most stable one. The additional stability is traced to the presence of oxygen dimers in K(2)O(2) which interact to form molecular orbitals. Other oxides such as KO(2) and KO(3) which also have dimers/trimers of oxygens are found to be less stable. This is traced to the shorter O-O bonds that one finds in them which gives rise to a significant coulomb repulsion between the electrons on the oxygen atoms making up the dimer/trimer, making them less stable.

Reduction of oxygen impurity at GaN/beta-Si(3)N(4)/Si interface via SiO(2) to Ga(2)O conversion by exposing of Si surface under Ga flux

The removal of native oxide from Si (1 1 1) surfaces was investigated by X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectra (SIMS) depth profiles. Two different oxide removal methods, performed under ultrahigh-vacuum (UHV) conditions, were carried out and compared. The first cleaning method is thermal desorption of oxide at 900 degrees C. The second method is the deposition of metallic gallium followed by redesorption. A significant decrease in oxygen was achieved by thermal desorption at 900 degrees C under UHV conditions. By applying a subsequent Ga deposition/redesorption, a further reduction in oxygen could be achieved. We examine the merits of an alternative oxide desorption method via conversion of the stable SiO(2) surface oxide into a volatile Ca(2)O oxide by a supply of Ga metals. Furthermore, ultra thin films of pure silicon nitride buffer layer were grown on a Si (1 1 1) surface by exposing the surface to radio-frequency (RF) nitrogen plasma followed by GaN growth. The SIMS depth profile shows that the oxygen impurity can be reduced at GaN/beta-Si(3)N(4)/Si interfaces by applying a subsequent Ga deposition/redesorption. (C) 2011 Elsevier B.V. All rights reserved.

Estimation of groundwater recharge of shallow aquifer on humid environment in Yaounde, Cameroon using hybrid water-fluctuation and hydrochemistry methods

A study of environmental chloride and groundwater balance has been carried out in order to estimate their relative value for measuring average groundwater recharge under a humid climatic environment with a relatively shallow water table. The hybrid water fluctuation method allowed the split of the hydrologic year into two seasons of recharge (wet season) and no recharge (dry season) to appraise specific yield during the dry season and, second, to estimate recharge from the water table rise during the wet season. This well elaborated and suitable method has then been used as a standard to assess the effectiveness of the chloride method under forest humid climatic environment. Effective specific yield of 0.08 was obtained for the study area. It reflects an effective basin-wide process and is insensitive to local heterogeneities in the aquifer system. The hybrid water fluctuation method gives an average recharge value of 87.14 mm/year at the basin scale, which represents 5.7% of the annual rainfall. Recharge value estimated based on the chloride method varies between 16.24 and 236.95 mm/year with an average value of 108.45 mm/year. It represents 7% of the mean annual precipitation. The discrepancy observed between recharge value estimated by the hybrid water fluctuation and the chloride mass balance methods appears to be very important, which could imply the ineffectiveness of the chloride mass balance method for this present humid environment.

An ultra-stable Cu nanowire under thermo-mechanical loading: A molecular dynamic study

We report on the formation of a stable Body-Centered Heptahedral (BCH) crystalline nanobridge structure of diameter ~ 1nm under high strain rate tensile loading to a <100> Cu nanowire. Extensive Molecular Dynamics (MD) simulations are performed. Six different cross-sectional dimensions of Cu nanowires are analyzed, i.e. 0.3615 x 0.3615 nm2, 0.723 x 0.723 nm2, 1.0845 x 1.0845 nm2, 1.446 x 1.446 nm2, 1.8075 x 1.8075 nm2, and 2.169 x 2.169 nm2. The strain rates used in the present simulations are 1 x 109 s-1, 1 x 108 s-1, and 1 x 107 s-1. We have shown that the length of the nanobridge can be characterized by larger plastic strain. A large plastic deformation is an indication that the structure is highly stable. The BCH nanobridge structure also shows enhanced mechanical properties such as higher fracture toughness and higher failure strain. The effect of temperature, strain rate and size of the nanowire on the formation of BCH structure is also explained in details. We also show that the initial orientation of the nanowires play an important role on the formation of BCH crystalline structure. Results indicate that proper tailoring of temperature and strain rate during processing or in the device can lead to very long BCH nanobridge structure of Cu with enhanced mechanical properties, which may find potential application for nano-scale electronic circuits.

A family of Runge-Kutta based explicit methods for rotational dynamics

The present paper develops a family of explicit algorithms for rotational dynamics and presents their comparison with several existing methods. For rotational motion the configuration space is a non-linear manifold, not a Euclidean vector space. As a consequence the rotation vector and its time derivatives correspond to different tangent spaces of rotation manifold at different time instants. This renders the usual integration algorithms for Euclidean space inapplicable for rotation. In the present algorithms this problem is circumvented by relating the equation of motion to a particular tangent space. It has been accomplished with the help of already existing relation between rotation increments which belongs to two different tangent spaces. The suggested method could in principle make any integration algorithm on Euclidean space, applicable to rotation. However, the present paper is restricted only within explicit Runge-Kutta enabled to handle rotation. The algorithms developed here are explicit and hence computationally cheaper than implicit methods. Moreover, they appear to have much higher local accuracy and hence accurate in predicting any constants of motion for reasonably longer time. The numerical results for solutions as well as constants of motion, indicate superior performance by most of our algorithms, when compared to some of the currently known algorithms, namely ALGO-C1, STW, LIEMID[EA], MCG, SUBCYC-M.

A comparison of three methods for downscaling daily precipitation in the Punjab region

Many downscaling techniques have been developed in the past few years for projection of station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs) to assess the hydrological impacts of climate change. This article compares the performances of three downscaling methods, viz. conditional random field (CRF), K-nearest neighbour (KNN) and support vector machine (SVM) methods in downscaling precipitation in the Punjab region of India, belonging to the monsoon regime. The CRF model is a recently developed method for downscaling hydrological variables in a probabilistic framework, while the SVM model is a popular machine learning tool useful in terms of its ability to generalize and capture nonlinear relationships between predictors and predictand. The KNN model is an analogue-type method that queries days similar to a given feature vector from the training data and classifies future days by random sampling from a weighted set of K closest training examples. The models are applied for downscaling monsoon (June to September) daily precipitation at six locations in Punjab. Model performances with respect to reproduction of various statistics such as dry and wet spell length distributions, daily rainfall distribution, and intersite correlations are examined. It is found that the CRF and KNN models perform slightly better than the SVM model in reproducing most daily rainfall statistics. These models are then used to project future precipitation at the six locations. Output from the Canadian global climate model (CGCM3) GCM for three scenarios, viz. A1B, A2, and B1 is used for projection of future precipitation. The projections show a change in probability density functions of daily rainfall amount and changes in the wet and dry spell distributions of daily precipitation. Copyright (C) 2011 John Wiley & Sons, Ltd.