Removing Congo red (CR) is critical in wastewater treatment. We introduce a combination of electrocoagulation (EC) and electro-oxidation (EO) to address the elimination of CR. We also discuss the deposition of triple oxides (Cu–Mn–Ni) simultaneously on both anodic and cathodic graphite electrodes at constant current density. These electrodes efficiently worked as anodes in the EC-EO system. The EC-CO combination eliminated around 98 % of the CR dye and about 95 % of the Chemical Oxygen demand (COD), and similar results were obtained with the absence of NaCl. Thus, EC-EO is a promising technique to remove CR in an environmentally friendly pathway.

The Electro-Fenton oxidation process is one of the essential advanced electrochemical oxidation processes used to treat Phenol and its derivatives in wastewater. The Electro-Fenton oxidation process was carried out at an ambient temperature at different current density (2, 4, 6, 8 mA/cm²) for up to 6 h. Sodium Sulfate at a concentration of 0.05M was used as a supporting electrolyte, and 0.4 mM of Ferrous ion concentration (Fe²⁺) was used as a catalyst. The electrolyte cell consists of graphite modified by an electrodepositing layer of PbO₂ on its surface as anode and carbon fiber modified with Graphene as a cathode. The results indicated that Phenol concentration decreases with an increase in current dens

Room temperature ionic liquids show potential as an alternative to conventional organic membrane solvents mainly due to their properties of low vapour pressure, low volatility and they are often stable. In the present work, the technical feasibilities of room temperature ionic liquids as bulk liquid membranes for phenol removal were investigated experimentally. In this research several hydrophobic ionic liquids were synthesized at laboratory. These ionic liquids include (1-butyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide[Bmim][NTf₂], 1-Hexyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide[Hmim][NTf₂], 1-octyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide[Omim][NTf₂],1‐butyl

The removal of heavy metal ions from wastewater by sorptive flotation using Amberlite IR120 as a resin, and flotation column, was investigated. A combined two-stage process is proposed as an alternative of the heavy metals removal from aqueous solutions. The first stage is the sorption of heavy metals onto Amberlite IR120 followed by dispersed-air flotation. The sorption of metal ions on the resin, depending on contact time, pH, resin dosage, and initial metal concentration was studied in batch method .Various parameters such as pH, air flow rate, and surfactant concentration were investigated in the flotation stage. Sodium lauryl sulfate (SLS) and Hexadecyltrimethyl ammonium bromide (HTAB) were used as anionic and cationic surfactant re

Purpose Heavy metals are toxic pollutants released into the environment as a result of different industrial activities. Biosorption of heavy metals from aqueous solutions is a new technology for the treatment of industrial wastewater. The aim of the present research is to highlight the basic biosorption theory to heavy metal removal. Materials and methods Heterogeneous cultures mostly dried anaerobic bacteria, yeast (fungi), and protozoa were used as low-cost material to remove metallic cations Pb(II), Cr(III), and Cd(II) from synthetic wastewater. Competitive biosorption of these metals was studied. Results The main biosorption mechanisms were complexation and physical adsorption onto natural active functional groups. It is observed that

In this study, we fabricated nanofiltration membranes using the electrospinning technique, employing pure PAN and a mixed matrix of PAN/HPMC. The PAN nanofibrous membranes with a concentration of 13wt% were prepared and blended with different concentrations of HPMC in the solvent N, N-Dimethylformamide (DMF). We conducted a comprehensive analysis of these membranes' surface morphology, chemical composition, wettability, and porosity and compared the results. The findings indicated that the inclusion of HPMC in the PAN membranes led to a reduction in surface porosity and fiber size. The contact angle decreased, indicating increased surface hydrophilicity, which can enhance flux and reduce fouling tendencies. Subsequently, we evaluated the e

Desalination is a process where fresh water produces from high salinity solutions, many ways used for this purpose and one of the most important processes is membrane distillation (MD). Direct contact membrane distillation (DCMD) can be considered as the most prominent type from MD types according to ease of design and modus operandi. This work studies the efficiency of using DCMD operation for desalination brine with different concentration (1.75, 3.5, 5 wt. % NaCl). Frame and plate cell was used with flat sheet PTFE hydrophobic type membrane. The study proves that MD is an effective process for desalination brines with feed temperature less than 60˚C especially for feed with low TDS. 37˚C, 47˚C, and 57˚C was feed t

In this study tungsten oxide and graphene oxide (GO-WO2.89) were successfully combined using the ultra-sonication method and embedded with polyphenylsulfone (PPSU) to prepare novel low-fouling membranes for ultrafiltration applications. The properties of the modified membranes and performance were investigated using Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), contact angle (CA), water permeation flux, and bovine serum albumin (BSA) rejection. It was found that the modified PPSU membrane fabricated from 0.1 wt.% of GO-WO2.89 possessed the best characteristics, with a 40.82° contact angle and 92.94% porosity. The permeation flux of the best membrane was the highest. The pure water permeation f

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class