First-principles prediction of the structural and electronic properties of zinc blende GaNxAs1−x alloys

To investigate the structural and electronic properties of zinc blende GaN_xAs_1?x alloys, we performed full-potential linearized augmented plane wave (FP-LAPW) calculations based on density functional theory. We assessed GaN_xAs_1?x alloys for 0≤x≤1 using 16-atom special quasi-random structures. The generalized gradient approximation (GGA) of Wu and Cohen was used as the exchange correlation potential to calculate the structural and electronic properties of GaN_xAs_1?x. In addition, the alternative GGA proposed by Engel and Vosko and the modified Becke–Johnson potential were used for better reproduction of the band structure and electronic properties. The equilibrium lattice parameters and bulk modulus were calculated and analyzed for binary and ternary alloys. The lattice constants for GaN_xAs_1?x positively deviate from Vegard's law with an upward bowing parameter of ?0.4708 Å. All our materials are direct-bandgap semiconductors for which the valence band maximum is located at Γ_v and the conduction band minimum at Γ_c. We observed that the direct bandgap of GaN_xAs_1?x increases nonlinearly with x. To shed light on the bandgap trend for increasing nitrogen concentrations in GaN_xAs_1?x, we used the atoms-in-molecule formalism. Special attention was paid to the increase in charge transfer for the nitrogen atom and to ionicity as a function of increasing x concentration.     

Legacy of the Zeppelins: defining fabrics as engineering materials

This paper explores the foundation of fabric mechanics and reveals that the discipline was pioneered in the early 1900s during the era of the Zeppelins, not by textile but by aeronautical engineers who wanted to predict the behavior of the outer shell of airships covered by fabric. The work of Haas is given particular attention in the context of his cloth model and in relation to the models of Ashenhurst and Peirce. This paper establishes a timeline of the early work on fabric mechanics by Ashenhurst, Armitage, Haas, Barker, and Peirce. It shows with clarity the differences and similarities of those early cloth models and it concludes that although our gratitude is due to all of these men for their unquestionable contributions, it was the aeronautical engineers who identified the conditions for the need of predicting fabric behavior and it was Haas’ cloth model in particular that laid the first foundation stone of this field.     

Flow condensation in parallel micro-channels – Part 1: Experimental results and assessment of pressure drop correlations

In this first part of a two-part study, experiments were performed to investigate condensation of FC-72 along parallel, square micro-channels with a hydraulic diameter of 1 mm and a length of 29.9 cm, which were formed in the top surface of a solid copper plate. The condensation was achieved by rejecting heat to a counter flow of water through channels brazed to the underside of the copper plate. The FC-72 entered the micro-channels slightly superheated, and operating conditions included FC-72 mass velocities of 68–367 kg/m² s, FC-72 saturation temperatures of 57.2–62.3 °C, and water mass flow rates of 3–6 g/s. Using high-speed video imaging and photomicrographic techniques, five distinct flow regimes were identified: smooth-annular, wavy-annular, transition, slug, and bubbly, with the smooth-annular and wavy-annular regimes being most prevalent. A detailed pressure model is presented which includes all components of pressure drop across the micro-channel. Different sub-models for the frictional and accelerational pressure gradients are examined using the homogenous equilibrium model (with different two-phase friction factor relations) as well as previous macro-channel and mini/micro-channel separated flow correlations. Unexpectedly, the homogenous flow model provided far more accurate predictions of pressure drop than the separated flow models. Among the separated flow models, better predictions were achieved with those for adiabatic and mini/micro-channels than those for flow boiling and macro-channels.     

Geochemistry of the sediments of the El-Kabir River and Akkar watershed in Syria and Lebanon

A total of 39 sediment samples were collected from the El‐Kabir River and its major tributaries during the low‐flow period of August/September 2001. Of these samples, six were selected for a scan for pesticide residues, polychlorinated biphenyls and polycyclic aromatic hydrocarbons (PAHs). An additional seven samples were analysed for major elements and trace elements. Despite the limited number of samples analysed, it can be concluded that major elements reflect the distribution and chemistry of major rock types in the watershed, the sodium oxide concentrations indicate an early onset of salinization in the coastal plain, dichlorodiphenyltrichloroethane is currently in use in the watershed despite being a banned substance, the PAH contamination is directly linked to an old, disused railway track, and chromium and nickel are the two trace elements showing anthropogenic enrichment, being attributed to leather tanning and metal plating by small‐scale industries in the watershed.     

Linear Programming-Based Affinity Scheduling of Independent Tasks on Heterogeneous Computing Systems

Resource management systems (RMS) are an important component in heterogeneous computing (HC) systems. One of the jobs of an RMS is the mapping of arriving tasks onto the machines of the HC system. Many different mapping heuristics have been proposed in recent years. However, most of these heuristics suffer from several limitations. One of these limitations is the performance degradation that results from using outdated global information about the status of all machines in the HC system. This paper proposes several heuristics which address this limitation by only requiring partial information in making the mapping decisions. These heuristics utilize the solution to a linear programming (LP) problem which maximizes the system capacity. Simulation results show that our heuristics perform very competitively while requiring dramatically less information.     

Drilling wear detection and classification using vibration signals and artificial neural network

In automated flexible manufacturing systems the detection of tool wear during the cutting process is one of the most important considerations. This study presents a comparison between several architectures of the multi-layer feed-forward neural network with a back propagation training algorithm for tool condition monitoring (TCM) of twist drill wear. The algorithm utilizes vibration signature analysis as the main and only source of information from the machining process. The objective of the proposed study is to produce a TCM system that will lead to a more efficient and economical drilling tool usage. Five different drill wear conditions were artificially introduced to the neural network for prediction and classification. The experimental procedure for acquiring vibration data and extracting features in both the time and frequency domains to train and test the neural network models is detailed. It was found that the frequency domain features, such as the averaged harmonic wavelet coefficients and the maximum entropy spectrum peaks, are more efficient in training the neural network than the time domain statistical moments. The results demonstrate the effectiveness and robustness of using the vibration signals in a supervised neural network for drill wear detection and classification.     

Quasi-Isotropic Triaxially Braided Cellulose-Reinforced Composites

In this article, we investigate experimentally and analytically the mechanical properties of a natural fiber quasi-isotropic triaxially braided composite. The composite is prepared from triaxially braided regenerated cellulose fibers and a high-bio-content epoxy resin system using a resin infusion process. Simultaneous mechanical loading, digital image correlation, and acoustic emission tests were performed on notched and unnotched specimens to understand the tensile behavior of the composites and the initiation and propagation of damage. Experimental results were compared with the effective tensile properties determined using an analytical model. The model is a discrete three-layer analytical representation based on a mechanics transformation-based representation of the quasi-isotropic braided layers. The model is used to determine the elastic stiffness and Poisson effects based on the constituent properties such as the fiber volume fractions, the waviness of the bias tows, and the relative thickness of the braided preform. The experimental results show the analytical model's ability in predicting the composite's elastic properties. The unique fabric architecture is found to have a large influence on the strength properties across the different specimen geometries investigated.     

Combinatorial study of NaF addition in CIGSe films for high efficiency solar cells

We report on a sodium fluoride (NaF) thickness variation study for the H₂Se batch furnace selenization of sputtered Cu(In,Ga) films in a wide range of Cu(In,Ga) film compositions to form Cu(In,Ga)Se₂ (CIGSe) films and solar cells. Literature review indicates lack of consensus on the mechanisms involved in Na altering CIGSe film properties. In this work, for sputtered and batch‐selenized CIGSe, NaF addition results in reduced gallium content and an increase in grain size for the top portion of the CIGSe film, as observed by scanning electron microscopy and secondary ion mass spectrometry. The addition of up to 20 nm of NaF resulted in an improvement in all relevant device parameters: open‐circuit voltage, short‐circuit current, and fill factor. The best results were found for 15 nm NaF addition, resulting in solar cells with 16.0% active‐area efficiency (without anti‐reflective coating) at open‐circuit voltage (V_OC) of 674 mV. Copyright © 2013 John Wiley & Sons, Ltd.