Structural and optical properties of TiO2 thin films grown by sol-gel dip coating process

The mono and bi-layer TiO₂ thin films have been prepared by sol-gel method on glass. X-Ray diffraction, Raman spectroscopy, atomic force microscopy, spectroscopic ellipsometry and m-lines spectroscopy techniques have been used to characterize the TiO₂ films. The mono-layer film is found to be amorphous, while the bi-layer film shows the presence of anatase phase. The bi-layer film exhibits more homogeneous surface with less roughness. The thickness effect on the refractive index, extinction ceofficient, packing density and optical band gap is analysed. The waveguiding measurements of the bi-layer film exhibit single-guided TE₀ and TM₀ polarized modes from which we can measure the refractive index and the film thickness.     

Numerische und experimentelle Untersuchungen zum Pulverpressen von Aluminium

Numerical and Experimental Investigations of Aluminium Powder Compaction The FEM simulation is a powerful means which can drastically reduce the time to production and costs in the optimization of powder forming processes. The current paper investigates experimentally and numerically die compaction of aluminium powder. The plastic deformation is formulated by using the Drucker‐Prager‐Cap‐model. This yield criterion describes the compressibility of porous bodies and allows the prediction of crack formation in the green compact. Axial compaction tests have been performed to determine material parameters for hardening. Simulation examples are presented to demonstrate the ability of the model to compute the distribution of the relative density. Furthermore, the compaction of an axisymmetric workpiece was simulated in order to determine optimal tools kinematics and to avoid crack formation.     

Toward an integrated dynamic defense system for strategic detecting attacks in cloud networks using stochastic game

Telecommunication Systems - In a complex network as a cloud computing environment, security is becoming increasingly based on deception techniques. To date, the static nature of cyber networks...     

Stacked neural networks for predicting the membranes performance by treating the pharmaceutical active compounds

Neural Computing and Applications - The removal of pharmaceutical actives compounds (PhACs) by nanofiltration (NF) and reverse osmosis (RO) of paramount importance in membrane separation processes....     

Computational intelligence techniques for modeling of dynamic adsorption of organic pollutants on activated carbon

Neural Computing and Applications - The objective of this work is to compare the efficiency of three computational intelligence techniques: Artificial Neural Networks (ANNs), Support Vector...     

FEM Simulation der Prozessschritte Pulverpressen/Sintern

FEM‐Simulation of the sequence Powder Pressing/Sintering The optimisation of powder forming processes is currently based on trial‐and‐error methods. Numerical simulation is a promising tool for reducing production times and costs. Particularly, the Finite Element Method (FEM) is a powerful tool for the simulation of metal forming processes. Within the scope of this work the simulation of powder die compaction for magnesium alloys was formulated by means of an elliptical yield criterion since this theory takes into account the compressibility of porous bodies by plastic deformation. The sintering process was modelled by using constitutive equations which are derived from a time‐dependent creep‐potential. Both models were implemented in a general purpose FEM‐code. In order to demonstrate the capability and numerical stability of the integration algorithms some powder metallurgical processes were simulated. The numerical simulation of the PM sequence die compaction/sintering allows the prediction of the workpiece's quality and the identification of the optimal process parameters. The implemented models enable the computation of the relative density distribution and the prediction of the shape distortion of the green during sintering. Furthermore, The possibility of the sintering process with non‐isothermal conditions and its influence on the shape distortion is demonstrated in this paper.     

Particle dispersion modeling in ventilated room using artificial neural network

Due to insufficiency of a platform based on experimental results for numerical simulation validation using computational fluid dynamic method (CFD) for different geometries and conditions,in this paper we propose a modeling approach based on the artificial neural network (ANN) to describe spatial distribution of the particles concentration in an indoor environment.This study was performed for a stationary flow regime.The database used to build the ANN model was deducted from bibliography literature and composed by 261 points of experimental measurement.Multilayer perceptron-type neural network (MLP-ANN) model was developed to map the relation between the input variables and the outputs.Several training algorithms were tested to give a choice of the Fletcher conjugate gradient algorithm (TrainCgf).The predictive ability of the results determined by simulation of the ANN model was compared with the results simulated by the CFD approach.The developed neural network was beneficial and easy to predict the particle dispersion curves compared to CFD model.The average absolute error given by the ANN model does not reach 5％ against 18％ by the Lagrangian model and 28％ by the Euler drift-flux model of the CFD approach.     

Spray Pyrolysis Synthesized and ZnO–NiO Nanostructured Thin Films Analysis with Their Nanocomposites for Waveguiding Applications

Semiconductors - In this work, we have prepared ZnO, NiO, and nanocomposites ZnO–NiO thin films elaborated by the chemical method of spray pyrolysis on glass substrates at a temperature of...     

Preparation of Sb:SnO2 thin films and its effect on opto-electrical properties

The present study focuses on pure and antimony (Sb)-doped tin oxide thin film and its influence on their structural, optical, and electrical properties. Both undoped and Sb-doped SnO₂ thin films have been grown by using simple, inexpensive pyrolysis spray technique. The deposition temperature was optimized to 450 °C. X-ray diffractions pattern have revealed that the films are polycrystalline and have tetragonal rutile-type crystal structure. Undoped SnO₂ films grow along (110) preferred orientation, while the Sb-doped SnO₂ films grow along (200) direction. The size of Sb-doped tin oxide crystals changes from 26.3 to 58.0 nm when dopant concentration is changed from 5 to 25 wt%. The transmission spectra revealed that all the samples are transparent in the visible region, and the optical bandgap varies between 3.92 and 3.98 eV. SEM analysis shows that the surface morphology and grain size are affected by the doping rate. All the films exhibit a high transmittance in the visible region and show a sharp fundamental absorption edge at about 0.38–0.40 nm. The maximum electrical conductivity of 362.5 S/cm was obtained for the film doped with 5 wt% Sb. However, the carrier concentration is increased from 0.708?×?10¹⁸ to 4.058?×?10²⁰ cm³. The electrical study reveals that the films have n-type electrical conductivity and depend on Sb concentration. We observed a decrease in sheet resistance and resistivity with the increase in Sb dopant concentration. For the dopant concentration of 5 wt% of Sb in SnO₂, the Rs and ρ were found minimum with the values of 88.55 (Ω cm^?2) and 2.75 (Ω cm), respectively. We observed an increase in carrier concentration and a decrease in mobility with the addition of Sb up to 25 wt%. The highest figure of merit values 2.5?×?10^–3 Ω^?1 is obtained for the 5wt% Sb, which may be considered potential materials for solar cells' transparent windows.

     

Novel approach for estimating solubility of solid drugs in supercritical carbon dioxide and critical properties using direct and inverse artificial neural network (ANN)

Neural Computing and Applications - In this work, a hybrid method based on neural network and particle swarm optimization (PSO) was applied to literature data to develop and validate a model that...