The escalating generation of industrial waste alongside the growing demand for high-performance, environmentally sustainable drilling fluids presents critical challenges to the oil and gas sector. Conventional drilling fluid additives are predominantly synthesized from virgin materials, contributing to resource depletion and environmental burden. Objectives: This study pioneers a circular economy approach by synthesizing silica nanoparticles (SiO2NPS) and alumina nanoparticles (Al2O3NPs) entirely from locally sourced industrial waste — bentonite clay and aluminum scrap, respectively — and evaluating their performance as functional additives in water-based drilling fluids (WBDFs). Novelty: To the best of our knowledge, this represents th

Increased diseases and obesity currently due to increased production and excessive consumption of foods manufactured from non-food sweeteners without attention to the risk of consuming those additional high calories due to consuming these refreshing products such as juices and other various drinks, especially in the summer season by most segments of Iraqi society, especially workers, children and school students the aim of this study. Therefore, the study designed to replace sucrose with 0.03, 0.04 and 0.05% of each of the white stevia crystals and milled dry stevia leaves in the laboratory manufacture of juices and its effect on the general and sensory characteristics and the extent of their acceptability among the specialized r

Spatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati

The increasing global energy demand and environmental concerns necessitate the development of sustainable energy storage solutions. Sodium-ion batteries have emerged as a promising alternative to lithium-ion batteries due to the abundance and low cost of sodium. This study investigates the impact of incorporating hybrid nanoparticles, specifically polyhedral oligomeric silsesquioxane- poly(ethylene glycol) (POSS-PEG(13.3)), on the performance of polyethylene oxide (PEO)- sodium perchlorate (NaClO4) based solid polymer electrolytes (SPEs). The results demonstrate that the incorporation of POSS-PEG(13.3) effectively disrupts the crystallinity of the PEO matrix, as confirmed by X-ray diffraction and differential scanning calorimetry analyses.

This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed