This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets. Overall, the findings highlight AI’s potential to improve productivity, lower carbon footprints, and support the transition toward more efficient and sustainable energy systems. This work provides strategic insights for stakeholders seeking to align technological advancement with sustainable energy transition objectives.
In the current study, synthesis and characterization of silver nanoparticles (AgNPs) before and after functionalization with ampicillin antibiotic and their application as anti-pathogenic agents towards bacteria were investigated. AgNPs were synthesized by a green method from AgNO3 solution with glucose subjected to microwave radiation. Characterization of the nanoparticles was conducted using UV-Vis spectroscopy, scanning electron microscopy (SEM), zeta potential determination and Fourier transform infrared (FTIR) spectroscopy. From SEM analysis, the typical silver nanoparticle particle size was found to be 30 nm and Zeta potential measurements gave information about particle stability. Analysis of FTIR patterns and UV-VIS spectroscopy con
... Show MoreMetasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat
... Show MoreSpray pyrolysis technique (SPT) is employed to synthesize cadmium oxide nanostructure with 3% and 5% Cobalt concentrations. Films are deposited on a glass substrate at 350 ᵒC with 150 nm thickness. The XRD analysis revealed a polycrystalline nature with cubic structure and (111) preferred orientation. Structural parameters represent lattice spacing, crystallite size, lattice parameter and dislocation density. Homogeneous surfaces and regular distribution of atoms were showed by atomic force microscope (AFM) with 1.03 nm average roughness and 1.22 nm root mean square roughness. Optical properties illustrated a high transmittance more than 85% in the range of visible spectrum and decreased with Co concentration increasing. The absorption
... Show MoreRapid worldwide urbanization and drastic population growth have increased the demand for new road construction, which will cause a substantial amount of natural resources such as aggregates to be consumed. The use of recycled concrete aggregate could be one of the possible ways to offset the aggregate shortage problem and reduce environmental pollution. This paper reports an experimental study of unbound granular material using recycled concrete aggregate for pavement subbase construction. Five percentages of recycled concrete aggregate obtained from two different sources with an originally designed compressive strength of 20–30 MPa as well as 31–40 MPa at three particle size levels, i.e., coarse, fine, and extra fine, were test
... Show MoreThe mechanism of the electronic flow rate at Al-TiO2 interfaces system has been studied using the postulate of electronic quantum theory. The different structural of two materials lead to suggestion the continuum energy level for Al metal and TiO2 semiconductor. The electronic flow rate at the Al-TiO2 complex has affected by transition energy, coupling strength and contact at the interface of two materials. The flow charge rate at Al-TiO2 is increased by increasing coupling strength and decreasing transition energy.
The dynamic behavior of laced reinforced concrete (LRC) T‐beams could give high‐energy absorption capabilities without significantly affecting the cost, which was offered through a combination of high strength and ductile response. In this paper, LRC T‐beams, composed of inclined continuous reinforcement on each side of the beam, were investigated to maintain high deformations as predicted in blast resistance. The beams were tested under four‐point loading to create pure bending zones and obtain the ultimate flexural capacities. Transverse reinforcement using lacing reinforcement and conventional vertical stirrups were compared in terms of deformation, strain, and toughness changes of the tes