The removal of congo red (CR) is a critical issue in contemporary textile industry wastewater treatment. The current study introduces a combined electrochemical process of electrocoagulation (EC) and electro-oxidation (EO) to address the elimination of this dye. Moreover, it discusses the formation of a triple composite of Co, Mn, and Ni oxides by depositing fixed salt ratios (1:1:1) of these oxides in an electrolysis cell at a constant current density of 25 mA/cm2. The deposition ended within 3 hours at room temperature. X-ray diffractometer (XRD), field emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), and energy dispersive X-ray (EDX) characterized the structural and surface morphology of the multi-oxide sediment. Marvelously, the deposition has simultaneously occurred on both anodic and cathodic graphite electrodes. These electrodes besides aluminum (Al) are employed as anodes in the EC-EO system, and the results were optimized by response surface methodology (RSM). The optimum operating conditions were a current density of 6 mA/cm2, pH = 7, and NaCl of 0.26 g/L. The results showed that the combined system eliminated more than 99.91% of the congo red dye with a removal of chemical oxygen demand (COD) of around 97% with 1.64 kWh/kg of dye of the consumed energy. At low current density, the current delivered for the composite anode was more than for the Al anode with the same surface area. On top of this superiority, the EC-EO scenario is a practical hybrid process to remove CR in an environmentally friendly pathway.
The thermoelectric power as a function of temperature for the Iron-Manganese-Aluminum, Fe-Mn-Al, alloys for manganese concentrations 0.04, 0.06, 0.08, 0.10 and 0.20 have been investigated in the temperature range 300 K. to 500 K. these results showed that the thermoelectric power coefficient in hot probe measurements showed that the electrons are the majority charge carriers in these alloys.
Phosphorus is usually the limiting nutrient for eutrophication in inland receiving waters; therefore, phosphorus concentrations must be controlled. In the present study, a series of jar test was conducted to evaluate the optimum pH, dosage and performance parameters for coagulants alum and calcium chloride. Phosphorus removal by alum was found to be highly pH dependent with an optimum pH of 5.7-6. At this pH an alum dosage of 80 mg/l removed 83 % of the total phosphorus. Better removal was achieved when the solution was buffered at pH = 6. Phosphorus removal was not affected by varying the slow mixing period; this is due to the fact that the reaction is relatively fast.
The dosage of calcium chloride and pH of solution play an importa
The purpose of this research was to prepare, characterize, and evaluate the new antimicrobial peptide KSL peptide encapsulated in poly(D,L-lactide-co-glycolide) (PLGA)composite microspheres. KSL was loaded in poly(acryloyl hydroxyethyl) starch (acHES) micropar-ticles, and then the peptide-containing microparticles were encapsulated in the PLGA matrix by a solvent extraction /evaporation method.
KSL-loaded PLGA microspheres were also prepared without the starch hydrogel microparticle microspheres for comparison study. KSL peptide microspheres were characterized for drug content, surface morphology, microspheres size determination, polymers stability , in vitro microspheres degradation and in vitro release. KSL peptide
... Show MoreA new tool geometry was used to achieve friction stir spot welding (FSSW) in which the shoulder was designed separately from the rotating pin, and in order to examine weldment strength through the modified tool, a lap joints of AA2024 aluminum alloy plate 1 mm thick were welded successfully by using 6 mm pin diameter and varying process parameters (rotational speeds, tool nose geometry, and depth of tool penetration in the lower welded plate). Experimental tests indicate that the maximum average tensile shear load was 3100 N at the best selected condition. Microstructure examination and micro hardness test along the spot zones were investigated as well as measuring pin penetration load. Visual inspection of the welded spot surface shows a g
... Show MoreAdsorption techniques are widely used to remove organics pollutants from waste water particularly, when using low cost adsorbent available in Iraq. Al-Khriet powder which was found in legs of Typha Domingensis is used as bio sorbent for removing phenolic compounds from aqueous solution. The influence of adsorbent dosage and contact time on removal percentage and adsorb ate amount of phenol and 4- nitro phenol onto Al-Khriet were studied. The highest adsorption capacity was for 4-nitrophenol 91.5% than for phenol 82% with 50 mg/L concentration, 0.5 gm. dosage of adsorbent and pH 6 under a batch condition. The experimental data were tested using different isotherm models. The results show that Freundlich model resulted in the best fit also
... Show MoreIn this study involves removing of Brilliant Dyes, were which (Brilliant Green {BG} and Brilliant Cresyl Blue {BCB}) by using Iraqi Siliceous Rocks Powder (SRP). Adsorption isotherms were studied and the factors which prefer it, like temperature and salt effect, Adsorption isotherms of dyes, Brilliant Cresyl Blue {BCB} was found to be comparable to Langmuir equation according to Giles classification, isotherms dye Brilliant Green {BG} was found to be comparable to Freundlich equation more than dye Brilliant Blue {BCB} according to Giles classification. The adsorption process on this surface (SRP) studied at different temperatures, the results showed that the adsorption of dyes (BCB, BG) on the surface increased with increased temperature (E
... Show MoreMachine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
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