Gholam Khayati
Department of Materials Science and Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
[ 1 ] - Adaptive neuro-fuzzy inference system and neural network in predicting the size of monodisperse silica and process optimization via simulated annealing algorithm
In this study, Back-propagation neural network (BPNN) and adaptive neuro-fuzzy inference system (ANFIS) methods were applied to estimate the particle size of silica prepared by sol-gel technique. Simulated annealing algorithm (SAA) employed to determine the optimum practical parameters of the silica production. Accordingly, the process parameters, i.e. tetraethyl orthosilicate (TEOS), H2O and N...
[ 2 ] - Hardness Optimization for Al6061-MWCNT Nanocomposite Prepared by Mechanical Alloying Using Artificial Neural Networks and Genetic Algorithm
Among artificial intelligence approaches, artificial neural networks (ANNs) and genetic algorithm (GA) are widely applied for modification of materials property in engineering science in large scale modeling. In this work artificial neural network (ANN) and genetic algorithm (GA) were applied to find the optimal conditions for achieving the maximum hardness of Al6061 reinforced by multiwall car...
[ 3 ] - Optimization of micro hardness of nanostructure Cu-Cr-Zr alloys prepared by the mechanical alloying using artificial neural networks and genetic algorithm
Cu–Cr-Zr alloys had wide applications in engineering applications such as electrical and welding industrial especially for their high strength, high electrical as well as acceptable thermal conductivities and melting points. It was possible to prepare the nano-structure of these age hardenable alloys using mechanical alloying method as a cheap and mass production technique to prepare the non-eq...
[ 4 ] - Modeling and Optimization of Roll-bonding Parameters for Bond Strength of Ti/Cu/Ti Clad Composites by Artificial Neural Networks and Genetic Algorithm
This paper deals with modeling and optimization of the roll-bonding process of Ti/Cu/Ti composite for determination of the best roll-bonding parameters leading to the maximum Ti/Cu bond strength by combination of neural network and genetic algorithm. An artificial neural network (ANN) program has been proposed to determine the effect of practical parameters, i.e., rolling temperature, reduction...
[ 5 ] - Artificial Neural Network Based Prediction Hardness of Al2024-Multiwall Carbon Nanotube Composite Prepared by Mechanical Alloying
In this study, artificial neural network was used to predict the microhardness of Al2024-multiwall carbon nanotube(MWCNT) composite prepared by mechanical alloying. Accordingly, the operational condition, i.e., the amount of reinforcement, ball to powder weight ratio, compaction pressure, milling time, time and temperature of sintering as well as vial speed were selected as independent input an...
[ 6 ] - Studying of Heat Treatment Influence on Corrosion Behavior of AA6061-T6 by Taguchi Method
In this study the Taguchi method, has been applied to optimize the heat treatment parameters for the corrosion resistance of AA6061 aluminum alloy. The experimental design consisted of four parameters (aging temperature, aging time, quenching environment and NaCl concentration), each containing three levels. Tafel polarization measurements were carried out to determine the corrosion resistance ...
[ 7 ] - A Novel Approach for Direct Preparation of Hydroxyapatite Nanoparticles from natural source using Microwave
Hydroxyapatite (HA) is one of the most common biocompatible ceramic with wide usages in various aspects of medicine due to the resemblance to the mineral bone tissue. The particle size of HA has a key roll in determination of the reaction rate at the interface of natural bones/artificial. Accordingly, this paper tries to propose a novel approach for the preparation of HA nanoparticles from natu...
[ 8 ] - Studying on the fatigue behavior of Al- Al2O3 metal matrix nano composites processed through powder metallurgy
Excellent mechanical properties and fatigue performance of Al/Al2O3 metal-based nanocomposites caused to introduce this material as a good candidate for various applications. In this regard, the preparation and characterization of this composite can be considered as a hot issue for research. The study was carried out in several steps including: (i) preparation of Al/Al2O3 metal-based nanocompos...
[ 9 ] - Characterization and DFT Studies for Green Synthesis of Silver Nanoparticles by Morphine Ampules and their Anti-proliferation Activity
This study is a green approach for the synthesis of silver nanoparticles (AgNPs) using morphine ampoules (MO) as reducing and capping agents. The toxicity effects of prepared particles were evaluated using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay on breast cancer cells. The spherical AgNPs with the average size of 50nm were synthesized and studied by UV–visible s...
[ 10 ] - Evaluating the Effect of the Number of Welding Passes on Microstructure, Hardness and Residual Stress of Ti-Al-Si Composite Coatings
The purpose of the present work is to investigate the influence of the number of weld-passes on microstructure, hardness and residual stresses of composite coatings composed of Ti-Al-Si intermetallic compounds. In this regard, surface coating of pure Ti was carried out using one and two passes of tungsten inert gas (TIG) welding with an Al filler alloy (grade 4043). Phase and structural evaluat...