In this work the strain energy of tetrahedrane and its nitrogen substituted molecules were calculated by isodesmic reaction method according to DFT quantum chemical fashion, the used basis set was 6-31G/B3-LYP, in addition all structures were optimized by RM1 semi-empirical method. From the obtained data we estimate an empirical equation connect between strain energy of the molecule with charge functions represented by dipole moment of the molecule plus accumulated charge density involved within the tetrahedron frame plus the number of nitrogen atoms. The results indicate the charge spreading factors by polarization and processes are the most important factors in decreasing the strain energy.

The drive of this exploration is to investigate the mucoadhesive assets of A. indica (Azadirachta indica) fruit mucilage by incorporating it into mucoadhesive microspheres with Acyclovir (AVR) as a model drug. The study was performed to check the impact of the mucilage proportion on particle size and swelling index. Nine batches of AVR mucoadhesive microspheres were made with varying proportions of Polyacrylic acid 934P and A. indica fruit mucilage (AIFM). A central composite design with design expert software to check the impact of dependent variables (A. indica mucilage and Polyacrylic acid 934 P levels) on particle size and swelling index as a response. As part of congeniality studies, the batches w

Background: This in vitro study compares a novel calcium-phosphate etchant paste to conventional 37% phosphoric acid gel for bonding metal and ceramic brackets by evaluating the shear bond strength, remnant adhesive and enamel damage following water storage, acid challenge and fatigue loading. Material and Methods: Metal and ceramic brackets were bonded to 240 extracted human premolars using two enamel conditioning protocols: conventional 37% phosphoric acid (PA) gel (control), and an acidic calcium-phosphate (CaP) paste. The CaP paste was prepared from β-tricalcium phosphate and monocalcium phosphate monohydrate powders mixed with 37% phosphoric acid solution, and the resulting phase was confirmed using FTIR. The bonded premolars were exp

Moisture damage is described as a reduction in stiffness and strength durability in asphalt mixtures due to moisture. This study investigated the influence of adding nano silica (NS) to the Asphalt on the moisture susceptibility of hot-mix-asphalt (HMA) mixtures under different aging conditions. NS was mixed with asphalt binder at concentrations of 2%, 4%, and 6% by weight of the binder. To detect the microstructure changes of modified Asphalt and estimate the dispersion of NS within the Asphalt, the field emission scanning electron microscope (FE-SEM) was used. To examine the performance of Asphalt mixed with NS at different aging stages (short-term and long-term aging), asphalt mixture tests such as Marshall stability,

High-volume traffic with ultra-heavy axle loads combined with extremely hot weather conditions increases the propagation of rutting in flexible pavement road networks. Several studies suggested using nanomaterials in asphalt modification to delay the deterioration of asphalt pavement. The current work aims to improve the resistance of hot mix asphalt (HMA) to rutting by incorporating Nano Silica (NS) in specific concentrations. NS was blended into asphalt mixtures in concentrations of 2, 4, and 6% by weight of the binder. The behavior of asphalt mixtures subjected to aging was investigated at different stages (short-term and long-term aging). The performance characteristics of the asphalt mixtures were evaluated using the Marshall s

 Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat

The utilization of sugarcane molasses (SCM), a byproduct of sugar refining, offers a promising bio-based alternative to conventional chemical admixtures in cementitious systems. This study investigates the effects of SCM at five dosage levels, 0.25%, 0.50%, 0.75%, 1.00%, and 1.25% by weight of cement, on cement mortar performance across fresh, mechanical, thermal, durability, and density criteria. A comprehensive experimental methodology was employed, including flow table testing, compressive strength (7, 14, and 28 days) and flexural strength measurements, embedded thermal sensors for real-time hydration monitoring, water absorption and chloride ion penetration tests, as well as 28-day density determination. Results revealed clear