Nanolayer CrAlN/TiSiN coating designed for tribological applications

With the goal to produce a hard and tough coating intended for tribological applications, CrAlN/TiSiN nanolayer coating was prepared by alternative deposition of CrAlN and TiSiN layers. In the first part of the article, a detailed study of phase composition, microstructure, and layer structure of CrAlN/TiSiN coating is presented. In the second part, its mechanical properties, fracture and tribological behavior are compared to the nanocomposite TiSiN coating. An industrial magnetron sputtering unit was used for coating deposition. X-ray photoelectron spectroscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, scanning electron microscopy, and transmission electron microscopy were used for compositional and microstructural analysis. Mechanical properties and fracture behavior were studied by instrumented indentation and focused ion beam techniques. Tribological properties were evaluated by ball-on-disk test in a linear reciprocal mode. A complex layer structure was found in the nanolayer coating. The TiSiN layers were epitaxially stabilized inside the coating which led to formation of dislocations at interfaces, to introduction of disturbances in the coating growth, and as a result, to development of fine-grained columnar microstructure. Indentation load required for the onset of fracture was twice lower for the nanolayer CrAlN/TiSiN, compared to the nanocomposite TiSiN coating. This agrees very well with their mechanical properties, with H³/E² being twice higher for the TiSiN coating. However, the nanolayer coating experienced less severe damage, which had a strong impact on tribological behavior. A magnitude of order lower wear rate and four times lower steady state friction coefficient were found for the nanolayer coating.     

Performance Investigations and PAPR Reduction Analysis Using Very Efficient and Optimized Amended SLM Algorithm for Wireless Communication OFDM System

Wireless Personal Communications - The orthogonal frequency division multiplexing (OFDM) is the most encouraging multi-carrier modulation system chosen for the high data rates but the objective is...     

Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

Experimental investigation of Co and Fe-Doped CuO nanostructured electrode material for remarkable electrochemical performance

The current research work presents a facile and cost–effective co-precipitation method to prepare doped (Co & Fe) CuO and undoped CuO nanostructures without usage of any type of surfactant or capping agents. The structural analysis reveals monoclinic crystal structure of synthesized pure CuO and doped-CuO nanostructures. The effect of different morphologies on the performance of supercapacitors has been found in CV (cyclic voltammetry) and GCD (galvanic charge discharge) investigations. The specific capacitances have been obtained 156 (±5) Fg^?1, 168(±5) Fg^?1 and 186 (±5) Fg^?1 for CuO, Co-doped CuO and Fe-doped CuO electrodes, respectively at scan rate of 5 mVs^?1, while it is found to be 114 (±5) Fg^?1, 136 (±5) Fg^?1 and 170 (±5) Fg^?1 for CuO, Co–CuO and Fe–CuO, respectively at 0.5 Ag^-1 as calculated from the GCD. The super capacitive performance of the Fe–CuO nanorods is mainly attributed to the synergism that evolves between CuO and Fe metal ion. The Fe-doped CuO with its nanorods like morphology provides superior specific capacitance value and excellent cyclic stability among all studied nanostructured electrodes. Consequently, it motivates to the use of Fe-doped CuO nanostructures as electrode material in the next generation energy storage devices.     

Synthesis,structure, CO oxidation,and H2 production activities of CaCu3−xMnxTi4−xMnxO12 (x = 0, 0.5, and 1.0)

Synthesis of nanocrystalline pristine and Mn-doped calcium copper titanate quadruple perovskites, CaCu_3?xMn_xTi_4?xMn_xO₁₂ (x = 0, 0.5, and 1.0) by modified citrate solution combustion method has been reported. Powder X-ray diffraction patterns attest the phase purity of the perovskite materials. Average particle sizes of all the materials obtained from the Scherrer's formula are in the range of 55–70 nm. The specific surface areas for all the perovskites obtained from BET isotherms are found to be low as expected for the condensed oxide systems and fall in the range of 13–17 m² g^?1. Transmission electron microscopy studies show a reduction in particle size of CaCu₃Ti₄O₁₂ with increase in Mn doping. Ca and Ti are present in +2 and +4 oxidation states in all the materials as demonstrated by X-ray photoelectron spectroscopy analyses. Cu²⁺ gets reduced in CaCu₃Ti₄O₁₂ with higher Mn content. Mn is observed to be present only in +3 oxidation state. All the materials have been examined to be active in CO oxidation as well as H₂ production from methanol steam reforming. CaCu₃Ti₄O₁₂ with ~14 at.% Mn is found to show best catalytic activities among these materials. A comprehensive analysis of the catalytic activities of these perovskites toward CO oxidation and H₂ production from MSR reveal the cooperative activity of copper-manganese in the doped perovskites and it is more effective at lower manganese content.     

The Influence of Magnetron Sputtering Conditions on the Structure of Zr–Pd Coatings

Technical Physics Letters - Using the method of DC magnetron sputtering, nonstructured amorphous metal coatings of Zr75Pd25 composition were obtained with an average deposition rate of 1.3 nm/s at...     

Privacy-preserving iris authentication using fully homomorphic encryption

Multimedia Tools and Applications - Rapid advancement in technology has led to the use of biometric authentication in every field. In particular, from the past few years, iris recognition systems...     

Situating natural language understanding within experience-based design

Building useful systems with an ability to understand "real" natural language input has long been an elusive goal for Artificial Intelligence. Well-known problems such as ambiguity, indirectness, and incompleteness of natural language inputs have thwarted efforts to build natural language interfaces to intelligent systems. In this article, we report on our work on a model of understanding natural language design specifications of physical devices such as simple electrical circuits. Our system, called KA, solves the classical problems of ambiguity, incompleteness and indirectness by exploiting the knowledge and problem-solving processes in the situation of designing simple physical devices. In addition, KA acquires its knowledge structures (apart from a basic ontology of devices) from the results of its problem-solving processes. Thus, KA can be bootstrapped to understand design specifications and user feedback about new devices using the knowledge structures it acquired from similar devices designed previously.In this paper, we report on three investigations in the KA project. Our first investigation demonstrates that KA can resolve ambiguities in design specifications as well as infer unarticulated requirements using the ontology, the knowledge structures, and the problem-solving processes provided by its design situation. The second investigation shows that KA's problem-solving capabilities help ascertain the relevance of indirect design specifications, and identify unspecified relations between detailed requirements. The third investigation demonstrates the extensibility of KA's theory of natural language understanding by showing that KA can interpret user feedback as well as design requirements. Our results demonstrate that situating language understanding in problem solving, such as device design in KA, provides effective solutions to unresolved problems in natural language processing.     

Some sulfides of gold and silver: Composition,mineral mineral assemblage,and conditions of formation

Characteristic mineral assemblage and special features of the composition of Au and Ag sulfides of gold-silver deposits have been established. The forms of the occurrence of Au and Ag in the minerals of the early and last stages have been analyzed. The conditions for the formation of uytenbogaardtite and petrovskaite in supergene and low-temperature hydrothermal processes have been considered. A thermodynamic model explaining their genesis in the oxidation zones is presented.