The aim of this study is to investigate the antibacterial capabilities of different coating durations of three nanoparticle (NP) coatings: molybdenum (Mo), tantalum (Ta), and zinc oxide (ZnO), and their effects on the surface characteristics of 316L stainless steel (SS). The coated substrates underwent characterization utilizing field emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectrometry (EDX), and X-ray diffractometer (XRD) techniques. The antibacterial efficacy of NPs was evaluated using the agar diffusion method. The FE-SEM and EDX images confirmed the presence of nano-sized particles of Mo, Ta, and ZnO on the surface of the substrates with perfectly symmetrical spheres and a uniform distribution of the NPs. All groups demonstrated antibacterial activity, and the ability to inhibit the growth of Streptococcus mutans and Lactobacillus acidophilus bacteria. The ZnO group had the most potent antibacterial effect, followed by the Mo group, while the Ta group had the least effect. A direct-current (DC) plasma sputtering system was used to produce nano-coatings of high purity that were homogeneous, crack-free and showed no sign of delamination. Bacterial strains exposed to Mo, Ta, and ZnO coated surfaces exhibited a significant loss of viability in a time-dependent manner. The optimum sputtering time to ensure the best antibacterial properties and preserve the resources was 1 hour (h) for Mo, 3 h for Ta and 6 h for ZnO.
Corrosion experiments were carried out to investigate the effect of several operating parameters on the corrosion rate and corrosion potential of carbon steel in turbulent flow conditions in the absence and presence of sodium benzoate inhibitor using electrochemical polarization technique. These parameters were rotational velocity (0 - 1.57 m/s), temperature (30oC – 50oC), and time. The effect of these parameters on the corrosion rate and inhibition efficiency were investigated and discussed. It was found that the corrosion rate represented by limiting current increases considerably with increasing velocity and temperature and that it decreased with time due to the formation of corrosion product layer. The corrosion potential shifted t
... Show MoreThe present work elucidates the utilization of activated carbon (AC) and activated carbon loaded with silver nanoparticles (AgNPs-AC) to remove tetracycline (TC) from synthetically polluted water. The activated carbon was prepared from tea residue and loaded with silver nanoparticles. Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET) were used to characterize the activated carbon (AC) and silver nanoparticles-loaded activated carbon (AgNPs-AC). The impact of various parameters on the adsorption effectiveness of TC was examined. These variables were the initial adsorbate concentration (Co), solution acidity (pH), adsorption time (t), and dosag
... Show MoreThis study was conducted on Lake Hamrin situated in Diyala governorate, focal Iraq, between latitudes 44º 53ʹ 26.16 '- 45º 07 ʹ 28.03ʺ and 34º 04ʹ 24.75ʺ ــ 34º 19ʹ 12.74ʺ . As in this study, the surface area of Hamrin Lake was calculated from satellite images during the period from October 2019 to September 2020, with an average satellite image for each month, furthermore,by utilizing the Normalized Differences Water Index (NDWI), the largest surface area was 264,617 km2 for October and the lowest surface area 140.202 km2 for September. The surface temperature of the lake water was also calculated from satellite images of the Landsat 8 satellite, based on ban
... Show MoreIn this work, a Photonic Crystal Fiber (PCF) sensor based on the Surface Plasmon Resonance (SPR) technology was proposed. A thin layer of gold (Au) was deposited on a D-shaped Photonic Crystal Fiber (PCF), which was coated with plasmonic chemically stable gold material with a thickness of 40nm. The performance parameters like sensitivity including wavelength sensitivity and amplitude sensitivity and resolution were evaluated by simulation using COMSOL software. The proposed sensor was created by using the finite element approach, it is numerically examined. The results show that the surface of D-shaped Photonic Crystal Fiber coated with Au behaves as a sensor to detect the refractive index (IR) of toxic metal ions. The impacts of the str
... Show MoreIrrigation has significant role in endodontic treatment, many types of antimicrobial irrigation solutions have been used, but due to the ineffectiveness, safety concerns and side effects of this irrigation, the herbal alternatives for endodontic irrigants might be beneficial. Objectives This study compared the in vitro effectiveness of tea tree oil and clove oil as possible irrigants in endodontics against Enterococcus faecalis in comparison with 3% Sodium hypochlorite. Materials and Methods E. faecalis was isolated from patients in need for endodontic treatment; VITEK was employed for E. faecalis isolate conformation. Muller Hinton agar was prepared with 100μl of freshly prepared suspension of E.faecalis. Wells of 6mm diameter and 4mm dep
... Show MoreIrrigation has significant role in endodontic treatment, many types of antimicrobial irrigation solutions have been used, but due to the ineffectiveness, safety concerns and side effects of this irrigation, the herbal alternatives for endodontic irrigants might be beneficial. Objectives This study compared the in vitro effectiveness of tea tree oil and clove oil as possible irrigants in endodontics against Enterococcus faecalis in comparison with 3% Sodium hypochlorite. Materials and Methods E. faecalis was isolated from patients in need for endodontic treatment; VITEK was employed for E. faecalis isolate conformation. Muller Hinton agar was prepared with 100μl of freshly prepared suspension of E.faecalis. Wells of 6mm diameter and 4mm dep
... Show MoreA three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
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