The Wheat husk is one of the common wastes abundantly available in the Middle East countries especially in Iraq. The present study aimed to evaluate the Wheat husk as low cost material, eco-friendly adsorbents for the removal of the carcinogenic dye (Congo red dye) from wastewater by investigate the effect of, at different conditions such as, pH(3-10), amount of adsorbents (1-2.3gm/L),and particle size (125-1000) μm, initial Congo red dye concentration(10, 25 , 50 and 75mg/l)  by batch experiments. The results showed that the removal percentage of dye increased with increasing adsorbent dosage, and decreasing particle size. The maximum removal and uptake reached (91%) , 21.5mg/g, respectively for 25 initial concent

The removal of direct blue 71 dye from a prepared wastewater was studied employing batch electrocoagulation (EC) cell. The electrodes of aluminum were used. The influence of process variables which include initial pH (2.0-12.0), wastewater conductivity (0.8 -12.57) mS/cm , initial dye concentration (30 -210) mg/L, electrolysis time  (3-12) min, current density (10-50) mA/cm2   were studied in order to maximize the color removal from wastewater. Experimental results showed that the color removal yield increases with increasing pH until pH 6.0 after that it decreased with increasing pH. The color removal increased with increasing current density, wastewater conductivity, electrolysis time, and decreased with increasing the concen

The purpose of this paper is to examine absorbance for the removal of the Red Congo using wheat husk as a biological pesticide. Several experiments have been conducted with the aim of configuring breakthrough data in a fluidized bed reactor. The minimum fluidized velocities of the bed were found to be 0.031 mm/s for mish sizes of (250) µm diameter with study the mass transfer be calculated K_L values. The results showed a well-fitting with the experimental data. Different operating conditions were selected: bed height (2, 5 and 10) cm, flow rate (90, 100and 120) ml/sec and particle diameter (250, 600, 1000) µm. The breakthrough curves were plotted for Congo Red, Values showed that the lower the bed, the lower the number of ad

This study was done to find a cheap, available and ecofriendly materials that can remove eosin y dye from aqueous solutions by adsorption in this study, two adsorbent materials were used, the shells of fresh water clam (Cabicula fluminea) and walnut shells. To make a comparison between the two adsorbents, five experiments were conducted. First, the effects of the contact time, here the nut shell removed the dye quickly, while the C. flumina need more contact time to remove the dye. Second, the effects of adsorbent weight were examined. The nut shell was very promising and for all used adsorbent weight, the R% ranged from 94.87 to 99.29. However C. fluminea was less effective in removing the dye with R% ranged from 47.59 to 55.39. The thi

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

The CIGS/CdS p-n junction thin films were fabricated and deposited at room temperature with rate of deposition 5, and 6 nm secG1 , on ITO glass substrates with 1mm thickness by thermal evaporation technique at high vacuum pressure 2×10G5 mbar, with area of 1 cm2 and Aluminum electrode as back contact. The thickness of absorber layer (CIGS) was 1 µm while the thickness of the window layer CdS film was 300 nm. The X-ray Diffraction results have shown that all thin films were polycrystalline with orientation of 112 and 211 for CIGS thin films and 111 for CdS films. The direct energy gaps for CIGS and CdS thin films were 1.85 and 2.4 eV, respectively. Atomic Force Microscopy measurement proves that both films CIGS and CdS films have nanostru