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 melting duration in the photovoltaic/phase-change material (PV/PCM) system is a crucial parameter for thermal energy management such that its improvement can realize better energy management in respect to thermal storage capabilities, thermal conditions, and the lifespan of PV modules. An innovative and efficient technique for improving the melting duration is the inclusion of an exterior metal foam layer in the PV/PCM system. For detailed investigations of utilizing different metal foam configurations in terms of their convective heat transfer coefficients, the present paper proposes a newly developed mathematical model for the PV/PCM–metal foam assembly that can readily be implemented with a wide range of operating condition
... Show MoreIn this paper two modifications on Kuznetsov model namely on growth rate law and fractional cell kill term are given. Laplace Adomian decomposition method is used to get the solution (volume of the tumor) as a function of time .Stability analysis is applied. For lung cancer the tumor will continue in growing in spite of the treatment.
Zeolite Y nanoparticles were synthesized by sol - gel method. Dffirent samples using two silica sources were prepared.
Sodium metasilicate (Na2SiO3) (48% silica) and silicic acid silica (H2SiO3) (75% silica) were employed as silica
source and aluminum nitrate (Al(NO3)3.9H2O) was the aluminum source with tetrapropylammonium hydroxide
(TPAOH) as templating agent.
The synihesized-samples were characterized by X-ray diffraction, showed the requirement of diffirent aging time for
complete crystallization to be achieved. Transmission Electronic Microscope (TEM) images, showed the particles were
in the same range of 30 - 75 nm. FT-IR spectroscory, showed the synthesized samples having the zeolite Y crystal
properties. The i
Two different composite materials were prepared by stir casting method of AA 6061 alloy as a matrix reinforced with two addition different ceramic materials Al2O3 and B4C of grain size 20 µm by 2.5, 5, 7.5 and10% in weight. The composite material with aluminum alloy as a matrix possesses a unique mechanical properties such as: high specific strength and hardness, low density, and high resistance to corrosion and friction wear. This composite is widely used in automotive parts space and marine applications.
Pin-on-disc technique was used to calculate the wear rate for each addition of Al2O3 and B4C particles. Rockwell hardness test and
... Show MoreIn this research study Hardness (shore D), Water absorption,
Flexural, Impact Test, and Fracture Toughness of polymer nano
composites. The polymer nano composites based on unsaturated
polyester resin reinforced with Kevlar fibers (K.F). The samples are
attended by hand lay – up method according to (Rule mixture) for
various volume fractions of unsaturated polyester resin, fiber and
carbon nanotube. The polyester resin was matrix strengthened with
3% volume fraction from Kevlar fiber and (0.5%, 1%, 1.5%, 2%)
volume fractions of carbon nanotube. The water absorption, hardness
(shore D), flexural test, impact test and toughness fracture properties
were studied. Results showed that the water absorption increas
In the present work, tetracycline (TC) was removed from a simulated wastewater through a new photo-anodic oxidation process with a rotating graphite cylinder anode. The effects of current density, pH, rotation speed, and NaCl addition were evaluated. The results confirmed that increasing the current density results in improving the removal of TC. However, increasing the current density beyond 5 mA/cm2 had little effect on TC removal. Results revealed that TC removal using photoanodic oxidation can be achieved at high performance with an initial pH of 5. Increasing or decreasing pH beyond this value has a negative effect on TC removal. Increasing rotation speed gave better performance for TC removal due to the increase in mass t
... Show MoreTo enhance interfacial bonding between carbon fibers and epoxy matrix, the carbon fibers have been modified with multiwall carbon nanotubes (MWCNTs) using the dip- coating technique. FT-IR spectrum of the MWCNTs shows a peak at 1640 cm−1 corresponding to the stretching mode of the C=C double bond which forms the framework of the carbon nanotube sidewall. The broad peak at 3430 cm−1 is due to O–H stretching vibration of hydroxyl groups and the peak at 1712 cm−1 corresponds to the carboxylic (C=O) group attached to the carbon fiber. The peaks at 2927 cm−1 and 2862 cm−1 ar
Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show MoreIn this work, some mechanical properties of the polymer coating were improved by preparing a hybrid system containing Graphene (GR) of different weight percentages (0.25, 0.5, 1, and 2wt%) with 5wt% carbon fibres (CF) and added to a polymer coating by using casting method. The properties were improved as GR was added with further improvement on adding 5wt% of CF. The impact strength of acrylic polymer with GR increases with increasing weight ratio of GR; maximum value was obtained when the polymer coating was incorporated with 1wt% GR and 5wt% CF. The impact strength of acrylic polymer with GR and GR/CF composites incorporated with GR at 1wt% and CF at 5wt%. Hardness increase with increasing weight ratio of Gr and a significant imp
... Show More