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Showing 7 results for Alam

Barzegar Alamdarit B., Ashrafi Zadeh S.n., Ashrafi Zadeh F.,
Volume 1, Issue 2 (Jan 2004)

In the current research, the optimum conditions for the electrolytic deposition of TiO2 coatings on titanium pieces were experimentally investigated. Flat pieces of commercially available titanium with dimensions of 50 x20 x3 mm were used as the anode and cathode electrodes. The coatings were applied on the cathode in an electrolyte solution essentially from water and methanol, containing different amounts of TiCI4, and H202. Coatings of sufficient thickness and adequate adhesion to the substrate were obtained at the optimum conditions of theELD process. The latter conditions were electrode gap distance of 3 cm, TiCl4 concentration of 0.005M, H202 concentration of 0.1 M, current density of 35 mA/cm2, methanol/water volume ratio of 9, and pH of the electrolyte in the vicinity of 1.40. Results of XRD analysis revealed the presence of anatase crystals of titanium oxide in the coated layers, where the deposited coating was treated at some temperatures in the range of 400 to 600°C for a period of at least 2 hours. Scanning electron microscopy (SEM) pictures also confirmed the formation of a uniform coating layer with cracked suiface area. At the optimum conditions of the process coatings with thicknesses of up to 10 flm were easily obtained through the application of one to three deposited layers.
M. Ghalambaz,, M. Shahmiri, Y. H. K Kharazi,
Volume 4, Issue 1 (winter & spring 2007 2007)

Abstract: Problems such as the difficulty of the selection of processing parameters and the large quantity of experimental work exist in the morphological evolutions of Semisolid Metal (SSM) processing. In order to deal with these existing problems, and to identify the effect of the processing parameters, (i.e. shearing rate-time-temperature) combinations on particle size and shape factor, based on experimental investigation, the Artificial Neural Network (ANN) was applied to predict particle size and shape factor SSM processed Aluminum A.356.0 alloy. The results clearly demonstrated that, the ANN with 2 hidden layers and topology (4, 2) can predict the shape factor and the particle size with high accuracy of 94%.The sensivity analysis also revealed that shear rate and solid fraction had the largest effect on shape factor and particle size, respectively. The shear rate had a reverse effect on particle size.
M. Ghalambaz, M. Shahmiri,
Volume 5, Issue 3 (Summer 2008 2008)

Abstract: Cooling slope-casting processing is a relatively new technique to produce semisolid cast feedstock for the thixoforming process. Simple equipment, ease of operation, and low processing costs are the main advantages of this process in comparison with existing processes such as mechanical stirring, electromagnetic stirring, etc. The processing parameters of cooling slope casting are length, angle and the material of the inclined plate and their combinations, which usually affect the micro structural evolutions of the primary solid phase. In order to clarify the effect of the processing parameters on the evolution of the particle size, based on experimental investigation, Artificial Neural Network (ANN) was applied to predict the primary silicon crystals (PSCs) size of semisolid cast ingot via a cooling slope casting process of Al-20%(wt.%) Si alloy. The results demonstrated that the ANN, with 2 hidden layers and topology (4, 3), could predict the primary particle size with a high accuracy of 94%. The sensitivity analysis also revealed that material of the cooling slope had the largest effect on particle size.
Mrs Somaye Alamolhoda, Dr Saeed Heshmati-Manesh, Dr Abolghasem Ataie,
Volume 7, Issue 3 (summer 2010 2010)

In this research an ultra-fine grained composite structure consisting of an intermetallic matrix together with dispersed nano-sized Al2O3 obtained via mechanical activation of TiO2 and Al in a high energy ball mill and sintering of consolidated samples. Phase composition and morphology of the milled and sintered samples were evaluated by XRD and SEM techniques Thermal behavior of the powder sample milled for 8 hours was evaluated by DTA technique. DTA results showed that, the reaction happens in two steps. The first step is the aluminothermic reduction of TiO2 with Al. XRD observations reveals that minor amount of Ti3Al phase formed during reduction reaction together with TiAl and Al2O3 major phases. This intermetallic phase disappeared when sintering temperature was increased to 850 ºC. The second step in DTA is related to a reaction between residual Al in the system (partly dissolved in TiAl lattice) and the Ti3Al phase produced earlier at lower temperatures. SEM micrographs reveal that by completion of the reduction reaction more homogeneous and finer microstructure is observable in sintered samples.
Z. Ghiami, S. M. Mirkazemi, S. Alamolhoda,
Volume 12, Issue 2 (June 2015)

trontium hexaferrite (SrFe 12 O 19 ) nanosized powders were synthesized by sol-gel auto-combustion method with and without cetyltrimethylammonium boromide (CTAB) addition in the sol with Fe/Sr ratio of 11 (using additional Sr). The resultant powders were investigated by X-ray Diffraction (XRD), Transmission Electron Microscope (TEM), Field Emission Scanning Electron Microscope (FESEM) and Vibration Sample Magnetometer (VSM) techniques. Phase constituents of the synthesized samples which were heat treated at temperatures in the range of 700- 900 ◦C were studied. XRD results revealed that CTAB addition facilitates the formation of single phase strontium hexaferrite at 800 ◦C. Microstructural evaluations with FESEM represented that CTAB addition causes formation of larger particles with a narrower size distribution. VSM results represented that the highest amount of intrinsic coercivity force ( i H C ) was obtained in the sample without CTAB addition and with additional Sr, calcined at 800 ◦C for 1 h which was equal to 5749.21 Oe, while the value of i H C was equal to 4950.89 Oe without additional Sr. The amount of maximum magnetization (M max ) was raised from 48.41 emu/g to 62.60 emu/g using CTAB and additional Sr. The microstructure and magnetic properties of the samples have been explained
S. Alamolhoda, S. M. Mirkazemi, T. Shahjooyi, N. Benvidi,
Volume 13, Issue 1 (March 2016)

Nano-sized NiFe2O4 powders were synthesized by sol–gel auto-combustion method using pH values from 7 to 9 in the sol. The effect of pH variations on complexing behavior of the species in the sol has been explained. Changes in phase constituents, microstructure and magnetic properties by changes in pH values were evaluated by X-ray diffraction (XRD), field emission scanning electron microscope (FESEM) and vibration sample magnetometer (VSM) techniques. Changes in pH value from 7 to 9 changes the amounts of NiFe2O4, FeNi3 and α-Fe2O3 phases. Calculated mean crystallite sizes are in the range of 44 to 51nm. FESEM micrographs revealed that increasing the pH value to 9 causes formation of coarse particles with higher crystallinity. Saturation magnetization was increased from 36.96emu/g to 39.35emu/g by increasing pH value from 7 to 8 which is the result of increased FeNi3 content. Using higher pH values in the sol reduces the Ms value.


Imtiaz Ali Soomro, Srinivasa Rao Pedapati, Mokhtar Awang, Afzal Ahmed Soomro, Mohammad Azad Alam, Bilawal Ahmed Bhayo,
Volume 19, Issue 4 (Desember 2022)

This paper investigated the optimization, modelling and effect of welding parameters on the tensile shear load bearing capacity of double pulse resistance spot welded DP590 steel. Optimization of  welding parameters was performed using the Taguchi design of experiment method. A relationship between input welding paramaters i.e., second pulse welding current, second pulse welding current time and first pulse holding time and output response i.e, tensile shear peak load was established using regression and neural network. Results showed that maximum average tensile shear peak load of 26.47 was achieved at optimum welding parameters i.e., second pulse welding current of 7.5 kA, second pulse welding time of 560 ms and first pulse holding time of 400 ms. It was also found that the ANN model predicted the tensile shear load with higher accuracy than the regression model.

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