A variety of oxides were examined as additives to a V2O5/Al2O3 catalyst in order to enhance the catalytic performance for the vapor phase oxidation of toluene to benzoic acid. It was found that the modification with MoO3 greatly promoted the little reaction leading to improve catalyst performance in terms of toluene conversion and benzoic acid selectivity. The effect of catalyst surface area, catalyst promoters, reaction temperature, O2/toluene, steam/toluene, space velocity, and catalyst composition to catalyst performance were examined in order to increase the benzoic acid selectivity and yield.

The aim of this work is to produce samples from Iraqi raw materials like Husyniat Bauxite (raw and burnt) and to study the effect of some additives like white Doekhla kaolin clays and alumina on that material properties were using sodium silica as a binding material. Five mixtures were prepared from Bauxite (raw and burnt) and kaolin clays, with an additive of (40) ml from sodium silica and alumina of (2.5, 5, 7.5,10 wt %) percentage as a binding material. the size grading was through sieving. The formation of all specimens was conducted by a measured gradually semi-dry pressing method under a compression force of (10) Tons and humidity ratio ranging from (5-10) % from mixture weight. Drying all specimens was done and then they were burn

This paper predicts the resilient modulus (Mr) for warm mix asphalt (WMA) mixtures prepared using aspha-min. Various predictor variables were analyzed, including asphalt cement types, asphalt contents, nominal maximum aggregate sizes (NMAS), filler content, test temperatures, and loading times. Univariate and multivariate analyses were conducted to examine the behavior of each predictor variable individually and collectively. Through univariate analysis, it was observed that Mr exhibited an inverse trend with asphalt cement grade, NMAS, test temperature, and load duration. Although Mr increased slightly with higher filler and asphalt content, the magnitude of this increase was minimal. Multivariate analysis revealed that the rate of change

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

Rutting is one of the most complex and widespread types of distress. The rutting is frequently observed on Iraqi roads, especially at the checkpoints, forming a significant hazard on the asphalt layers. Factors such as heavy loads and high temperatures contribute to this distress. Adding fibers to a hot mix asphalt (HMA) effectively improves performance and extends the lifespan of the flexible pavement. This article used glass, steel, and basalt fibers. The wheel tracking test assessed the fibre-asphalt mixture for rutting resistance and compared it with the mix without adding fibers (control HMA). Meanwhile, the microscopic structure of fibres and asphalt mixture modified with fibers was examined using the Field Emission Scanning E