The effect of using different R -molar ratio under variable reaction conditions (acidic as well as basic environment and reaction temperature) have been studied. The overall experiments are driven with open and closed systems. The study shows that there is an optimum value for a minimum gelling time at R equal 2. The gelling time for all studied open system found to be shorter than in closed system. In acidic environment and when R value increased from 2 to 10, the gelling time of closed systems has increased four times than open systems at T=30 ?C and fourteen times when temperature reaction increased to 60 ?C. While in basic environment the influence of increasing R value was limited.

Zinc Oxide (ZnO) thin films of different thickness were prepared
on ultrasonically cleaned corning glass substrate, by pulsed laser
deposition technique (PLD) at room temperature. Since most
application of ZnO thin film are certainly related to its optical
properties, so the optical properties of ZnO thin film in the
wavelength range (300-1100) nm were studied, it was observed that
all ZnO films have high transmittance (˃ 80 %) in the wavelength
region (400-1100) nm and it increase as the film thickness increase,
using the optical transmittance to calculate optical energy gap (Eg
opt)
show that (Eg
opt) of a direct allowed transition and its value nearly
constant (~ 3.2 eV) for all film thickness (150

Metasurface 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

The effect of three ionic liquids viz., 1-hexyl-3-methylimidazolium tetrafluoroborate (ILE), 1-hexyl-3-metylimidazolium hexafluorophosphate (ILF) and 1-octyl-3-methylimidazolium tetrafluoroborate (ILG) when used as surfactants on the performance of dissolved air floatation (DAF) was investigated.

   Experiments were conducted at a temperature of 30-35 ºC, 10ppm ferric chloride as coagulant, 50% recycle ratio, pH 8, and 10 minutes treatment time  to find oil and grease (OG) and turbidity removal efficiencies at saturation pressure (2-6) bar.

ILs were used at concentration of 50 µl/liter of treated water in two positions in DAF system; the saturation vessel and the treatment tank. The performance using ILs

The depletion of petroleum reserves and increasing environmental concerns have driven the development of eco-friendly asphalt binders. This research investigates the performance of natural asphalt (NA) modified with waste engine oil (WEO) as a sustainable alternative to conventional petroleum asphalt (PA). The study examines NA modified with 10%, 20%, and 30% WEO by the weight of asphalt to identify an optimal blend ratio that enhances the binder’s flexibility and workability while maintaining high-temperature stability. Comprehensive testing was conducted, including penetration, softening point, viscosity, ductility, multiple stress creep recovery (MSCR), linear amplitude sweep (LAS), energy-dispersive X-ray spectroscopy (EDX), F

Toxic substances have been released into water supplies in recent decades because of fast industrialization and population growth. Fenton electrochemical process has been addressed to treat wastewater which is very popular because of its high efficiency and straightforward design. One of the advanced oxidation processes (AOPs) is electro-Fenton (EF) process, and electrode material significantly affects its performance. Nickel foam was chosen as the source of electro-generated hydrogen peroxide (H2O2) due to its good characteristics. In the present study, the main goals were to explore the effects of operation parameters (FeSO4 concentration, current density, and electrolysis time) on the catalytic performance that was optimized by r

Toxic substances have been released into water supplies in recent decades because of fast industrialization and population growth. Fenton electrochemical process has been addressed to treat wastewater which is very popular because of its high efficiency and straightforward design. One of the advanced oxidation processes (AOPs) is electro-Fenton (EF) process, and electrode material significantly affects its performance. Nickel foam was chosen as the source of electro-generated hydrogen peroxide (H₂O₂) due to its good characteristics. In the present study, the main goals were to explore the effects of operation parameters (FeSO₄ concentration, current density, and electrolysis time) on the catalytic perform

Web testing is very important method for users and developers because it gives the ability to detect errors in applications and check their quality to perform services to users performance abilities, user interface, security and other different types of web testing that may occur in web application. This paper focuses on a major branch of the performance testing, which is called the load testing. Load testing depends on an important elements called request time and response time. From these elements, it can be decided if the performance time of a web application is good or not. In the experimental results, the load testing applied on the website (http://ihcoedu.uobaghdad.edu.iq) the main home page and all the science departments pages. In t

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

This study aimed to evaluate the effectiveness of a novel concrete-encased column (CE) using small circular steel tubes filled with cementitious grouting material (GFST) as the primary reinforcement instead of traditional steel bars. The research involved three different types of reinforcement: conventional steel bars, concrete-filled steel tubes with 30% of the reinforcement ratio of steel bars, and concrete-filled steel tubes with the same reinforcement ratio as steel bars. Twenty-four circular concrete columns were tested and categorized into six groups based on the type of reinforcement employed. Each group comprised four columns, with one subjected to concentric axial load, two subjected to eccentric axial load (with eccentrici