Deep eutectic solvents (DESs) are considered as relativity green solvents in comparison with ionic liquids and organic solvents. DESs are used in nanotechnology applications due to their unique physiochemical properties, efficient dispersants and they can be easily prepared in high purity at low cost. Other advantages include their nontoxicity, no reactivity with water and being biodegradable. DESs have recently attracted much attention in various fields, especially in the field of nanotechnology in controlling the size, surface chemistry and morphology of the nanomaterials and in the processing of advanced functional nanomaterials. As a result, various studies have been undertaken to investigate the physicochemical characteristics of the combination of DESs and nanomaterials. Recently, DESs are widely used as functionalization agents for different nanomaterials. Hence, this chapter will be summarizing the recent developments of DESs to improve the surface chemistry of nanomaterials and their possible applications.
Low- and medium-carbon structural steel components face random vibration and dynamic loads (like earthquakes) in many applications. Thus a modification to improve their mechanical properties, essentially damping properties, is required. The present study focuses on improving and developing these properties, significantly dampening properties, without losing the other mechanical properties. The specimens used in the present study are structural steel ribbed bar ISO 6935 subjected to heating temperatures of (850, 950, and 1050) ˚C, and cooling schemes of annealing, normalizing, sand, and quenching was selected. The damping properties of the specimens were measured experimentally with the area under the curve for the loadi
... Show MorePotentiostatic polarization and weight loss methods have been used to investigate the corrosion behavior of carbon steel in sodium chloride solution at different concentrations (0.1, 0.4 and 0.6) M under the influence of temperatures ( 293, 298, 303, 308 and 313) K. The inhibition efficiency of the amoxicillin drug on carbon steel in 0.6 M NaCl has also been studied based on concentration and temperature. The corrosion rate showed that all salt concentrations ( NaCl solution) resulted in corrosion of carbon steel in varying ratio and 0.6 M of salt solution was the highest rate (50.46 g/m².d). The results also indicate that the rate of corrosion increases at a temperature of 313 K.. Potentiodynamic polarization studi
... Show MoreIn this work, synthesized N4,N4`-bis(2, 3, 4 nitro benzylidene) biphenyi-4-4`-diamine(B1-B3) , was tested as an inhibitors in controlling the corrosion of carbon steel in NaCl 3.5% solution by using open circuit potential (OCP),at four different temperatures (293, 303, 313 and 323 K). Furthermore, the surface morphology was investigated using the Atomic force microscopy (AFM). The effect of using different Schiff bases and temperature was also investigated. Schiff bases was synthesized and characterized via using. Fourier Transform Infrared Spectroscopy (FT-IR)and Atomic Force Microscope (AFM) characterized . The experimental results shown that Schiff bases can consider as an excellent corrosion inhibitors for carbon steel in NaCl 3
... Show MoreRemoval of heavy metal ions such as, cadmium ion (Cd 2+) and lead ion (Pb 2+) from aqueous solution onto Eichhornia (water hyacinth) activated carbon (EAC) by physiochemical activation with potassium hydroxide (KOH) and carbon dioxide (CO2) as the activating agents were investigated. The Eichhornia activated carbon was characterized by Brunauer Emmett Teller (BET), Fourier Transform Infrared spectroscopy (FTIR), and Scanning Electron Microscopy (SEM) techniques. Whereas, the effect of adsorbent dosage, contact time of pH, and metal ion concentration on the adsorption process have been investigated using the batch process t
Due to the broad range uses of chromium for industrial purposes, besides its carcinogenic effect, an efficient, cost effective removal method should be obtained. In this study, cow bones as a cheap raw material were utilized to produce active carbon (CBAC) by physiochemical activation, which was characterized using: SEM to investigate surface morphology and BET to estimate the specific surface area. The best surface area of CBAC was 595.9 m2/gm which was prepared at 600 ᵒC activation temperature and impregnation ratio of 1:1.5. CBAC was used in aqueous chromium ions adsorption. The investigated factors and their ranges are: initial concentration (10-50 mg/L), adsorption time (30-300 min), temperature (20-50
... Show MoreA comparative study was carried out to evaluate alkaloid antibacterial activity which was extracted from the root bark Punica granatum L. by liquid membrane techniques (SA) and organic solvent traditional techniques (SB). The screening of the antimicrobial activity was conducted by agar well diffusion method against Staphylococcus aureus, Enterobacter cloacae, Escherichia coli, Klebsiella pneumoniae, and Proteus mirabilis at three concentration levels (5, 10 and 15 mg/ml). Alkaloid extracts were analyzed by a high performance liquid chromatography (HPLC) method. Among the tested extractions, SB showed the highest antibacterial activity against all five bacterial strains, especially at 15 mg/ml concentration. However, all the B type solution
... Show MoreThe study focused on the treatment of real oilfield produced water from the East Baghdad field affiliated to the Midland Oil Company (Iraq) using an oil skimming process followed by a coagulation/flocculation process for zero liquid discharge system applications. Belt type oil skimmer was utilized for evaluating the process efficiency with various operating conditions such as temperature (17-40 °C) and time (0.5-2.5 hr.). Polyaluminum chloride (PAC) coagulant and polyacrylamide (PAM) flocculant was used to investigate the performance of the coagulation/flocculation process with PAC dosage (5-90 ppm) and pH (5-10) as operating conditions. In the skimming process, the oil content, COD, turbidity, and TSS decreased with an increase in tempera
... Show MoreComputer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
... Show MoreRecently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural
... Show MoreAdverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD
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