The 3D electro-Fenton technique is, due to its high efficiency, one of the technologies suggested to eliminate organic pollutants in wastewater. The type of particle electrode used in the 3D electro-Fenton process is one of the most crucial variables because of its effect on the formation of reactive species and the source of iron ions. The electrolytic cell in the current study consisted of graphite as an anode, carbon fiber (CF) modified with graphene as a cathode, and iron foam particles as a third electrode. A response surface methodology (RSM) approach was used to optimize the 3D electro-Fenton process. The RSM results revealed that the quadratic model has a high R2 of 99.05 %. At 4 g L-1 iron foam particles, time of 5 h, and 1 g of graphene, the maximum efficiency of phenol removal of 92.58 % and chemical oxygen demand (COD) of 89.33 % were achieved with 32.976 kWh kg-1 phenol of consumed power. Based on the analysis of variance (ANOVA) results, the time has the highest impact on phenol removal efficiency, followed by iron foam and graphene dosage. In the present study, the 3D electro-Fenton technique with iron foam partials and carbon fiber modified with graphene was detected as a great choice for removing phenol from aqueous solutions due to its high efficiency, formation of highly reactive species, with excellent iron ions source electrode.
The influence and hazard of fire flame are one of the most important parameters that affecting the durability and strength of structural members. This research studied the influence of fire flame on the behavior of reinforced concrete beams affected by repeated load. Nine self- compacted reinforced concrete beams were castellated, all have the same geometric layout (0.15x0.15x1.00) m, reinforcement details and compressive strength (50 Mpa). To estimate the effect of fire flame disaster, four temperatures were adopted (200, 300, 400 and 500) oC and two method of cooling were used (graduated and sudden). In the first cooling method, graduated, the tested beams were leaved to cool in air while in the second method, sudden, water splash was use
... Show MoreIn this work, metal oxides nanostructures, mainly, copper oxide (CuO), nickel oxide (NiO), titanium dioxide (TiO2), and multilayer structure were synthesized by dc reactive magnetron sputtering technique. The structural purity and nanoparticle size of the prepared nanostructures were determined. The individual metal oxide samples (CuO, NiO and TiO2) showed high structural purity and minimum particle sizes of 34, 44, 61 nm, respectively. As well, the multilayer structure showed high structural purity as no elements or compounds other than the three oxides were founds in the final sample while the minimum particle size was 18 nm. This reduction in nanoparticle size can be considered as an advantage for the dc reactive magnetron sputtering tec
... Show MoreIn this work, a novel design for the NiO/TiO2 heterojunction solar cells is presented. Highly-pure nanopowders prepared by dc reactive magnetron sputtering technique were used to form the heterojunctions. The electrical characteristics of the proposed design were compared to those of a conventional thin film heterojunction design prepared by the same technique. A higher efficiency of 300% was achieved by the proposed design. This attempt can be considered as the first to fabricate solar cells from highly-pure nanopowders of two different semiconductors.
The study is based on the selective binding ability of the drug compound procaine (PRO) on a surface imprinted with nylon 6 (N6) polymer. Physical characterization of the polymer template was performed by X-ray diffraction and DSC thermal analysis. The imprinted polymer showed a high adsorption capacity to trap procaine (237 µg/g) and excellent recognition ability with an imprinted factor equal to 3.2. The method was applied to an extraction column simulating a solid-phase extraction to separate the drug compound in the presence of tinoxicam and nucleosimide separately and in a mixture of them with a recovery rate more than the presence of tinoxicam and nucleosimide separately and in a mixture of them with a recovery rate of more t
... Show MoreThis study aimed to see how allicin (45mg/kg BW) affected diabetic Mellitus in male rats (DM). Forty male rats were utilized, and they were split into four groups at random for 42 days. T2 was treated with 45 mg/kg B.W of allicin dissolved in 1 ml of D.W daily and injected with a single dose of sodium citrate buffer (0.5ml Intra-Peritoneal IP), DM was induced in T1 and T2 by injection of a single dose of streptozotocin 50 mg/kg B.W IP, T1 was assigned as a positive control, T3 received 45 mg/kg B.W. of allicin dissolved in 1 ml D.W. every day, and a single dose of sodium citrate buffer was injected (0.5ml IP). When diabetic rats treated with allicin in T2 were compared to diabetic rats in T1, the findings indicated a significant increase (P
... Show MoreThis work deals with thermal cracking of heavy vacuum gas oil which produced from the top of vacuum distillation unit at Al- DURA refinery, by continuous process. An experimental laboratory plant scale was constructed in laboratories of chemical engineering department, Al-Nahrain University and Baghdad University. The thermal cracking process was carried out at temperature ranges between 460-560oC and atmospheric pressure with liquid hourly space velocity (LHSV) equal to 15hr-1.The liquid product from thermal cracking unit was distilled by atmospheric distillation device according to ASTM D-86 in order to achieve two fractions, below 220oC as a gasoline fraction and above 220oC as light cycle o
... Show MoreTwitter data analysis is an emerging field of research that utilizes data collected from Twitter to address many issues such as disaster response, sentiment analysis, and demographic studies. The success of data analysis relies on collecting accurate and representative data of the studied group or phenomena to get the best results. Various twitter analysis applications rely on collecting the locations of the users sending the tweets, but this information is not always available. There are several attempts at estimating location based aspects of a tweet. However, there is a lack of attempts on investigating the data collection methods that are focused on location. In this paper, we investigate the two methods for obtaining location-based dat
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