Copper is a cheaper alternative to various noble metals with a range of potential applications in the field of nanoscience and nanotechnology. However, copper nanoparticles have major limitations, which include rapid oxidation on exposure to air. Therefore, alternative pathways have been developed to synthesize metal nanoparticles in the presence of polymers and surfactants as stabilizers, and to form coatings on the surface of nanoparticles. These surfactants and polymeric ligands are made from petrochemicals which are non- renewable. As fossil resources are limited, finding renewable and biodegradable alternative is promising.The study aimed at preparing, characterizing and evaluating the antibacterial properties of copper nanoparticles. Copper nanoparticles were prepared using gelatin biopolymer, CuSO4.5H2O ions and hydrazine as stabilizer, precursor salt and reducing agent respectively. However, vitamin C and NaOH solution were also employed as an antioxidant and pH adjuster. The synthesized copper nanoparticles were characterized using UV-visible spectroscopy (UV-vis), thermogravimetric analysis (TGA), zeta potential measurements powder, X-ray diffraction (XRD), field emission scanning electron microscope and transmission electron microscope (TEM). The UV-visible absorption spectrum confirms the formation of the CuNPs, which showed maximum absorbance at 583 nm. Results obtained from TEM indicated a decrease in size of particle from a low concentration to high concentration of the supporting materials. The optimum concentration of gelatin was found to be 0.75 wt%. The supporting materials used for this synthesis are biocompatible and the obtained products are stable in air. The synthesized CuNPs display promising antibacterial activities against B. subtilis (B29), S. aureus (S276), S. choleraesuis (ATCC 10708) and E. coli (E266) as gram positive and negative bacteria respectively.
Well integrity is a vital feature that should be upheld into the lifespan of the well, and one constituent of which casing, necessity to be capable to endure all the interior and outside loads. The casing, through its two basic essentials: casing design and casing depth adjustment, are fundamental to a unique wellbore that plays an important role in well integrity. Casing set depths are determined based on fracturing pressure and pore pressure in the well and can usually be obtained from well-specific information. Based on the analyzes using the improved techniques in this study, the following special proposition can be projected: The selection of the first class and materials must be done correctly and accurately in accordance with
... Show MoreThis study was aime to investigate the effect of addition different concentration of celery leaves to white soft cheese ,Treated cheese between 2018-2019, ,The finely Celery (Apium graveolens) leaves were adding to crude white cheese after texturizing in three leveles included (A,B,C) in addition of control antimicrobial activity of celery treated cheese against total account bacteria and coliform bacteria was estimated during (0, 5, 10, 15, 20) days. The results were shown that the higher concentration of celery in treated cheese, had a lower concentration of protein, lipid and ash content ( 16.81,15.13 and 4.30% respectively, but it had a higher moisture content 59.50%.also the total bacteria counts were decreasing significantly (0.05 P)w
... Show MoreNowadays, energy demand continuously rises while energy stocks are dwindling. Using current resources more effectively is crucial for the world. A wide method to effectively utilize energy is to generate electricity using thermal gas turbines (GT). One of the most important problems that gas turbines suffer from is high ambient air temperature especially in summer. The current paper details the effects of ambient conditions on the performance of a gas turbine through energy audits taking into account the influence of ambient conditions on the specific heat capacity ( , isentropic exponent ( ) as well as the gas constant of air . A computer program was developed to examine the operation of a power plant at various ambient temperature
... Show MoreStereo lithography (SLA) three-dimensional (3D) printing process is a type of additive manufacturing techniques that uses digital models from computer-aided design to automatically produce customized 3D objects. Around 30 years, it has been widely utilized in the manufacturing, design, engineering, industrial sectors and its applications in dentistry for manufacturing prosthodontics are very important. The stereo lithography technology is highly regarded because it can produce items with excellent precision especially when selecting the best process parameters. This review article offers a useful and scientific summary of SLA three-dimensional printing technology and its brief history. The specific type of 3D printers which is SLA t
... Show MoreThe global rise in temperature and the desert climatic conditions prevalent in Middle Eastern countries have exacerbated rutting distress in heavily trafficked highways. Conventional asphalt binders with a high-temperature performance grade (PG 70) have proven inadequate under such extreme conditions, necessitating the development of modified binders with enhanced high-temperature performance. While polymer modification using styrene-butadiene-styrene (SBS), an elastomeric polymer, and ethylene-vinyl acetate (EVA), a plastomeric polymer, has been widely studied, limited research provides a direct comparison of their effectiveness at both the binder and mixture levels under extremely high-temperature conditions. This study addresses this gap
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for