Applied Chemical Engineering

Abstract Borophosphate glasses with compositions xNa 2 O-(45-x) B 2 O 3 -45P 2 O 5 -10MnO, where x ranges from 5 to 25 mol%, have been prepared using the conventional melt quenching technique. Several methods including X-ray diffraction, Fourier transform infrared spectroscopy (FTIR), and differential scanning calorimetry (DSC) have been used to characterize the produced materials. The absence of crystalline structure in the prepared phosphate glasses was confirmed by X-ray diffraction (XRD) studies. The chemical resistance of these glasses increases with the Na 2 O content. Glasses containing more than 15 mol% Na 2 O have excellent chemical resistance. The relationship between structural changes and composition was investigated by measuring density and glass transition temperature Tg. The results obtained show that the glass transition temperature and chemical properties increase with increasing sodium oxide composition in all the glasses studied. These experimental results indicate that Na 2 O lowers the melting point and increases the strength of the glasses.

Abstract The aim of this article is to develop a "switchable hydrophilicity solvent liquid phase microextraction" (SHS-LPME) for the effectual extraction of fast green FCF. Three "switchable hydrophilicity solvents" (SHSs) were practiced for the extraction of fast green FCF. The attained extract phase afterward phase separation was evaluated by UV-VIS spectrophotometry. The extraction parameters such as, SHS volume, HNO3 volume and NaOH volume, were enhanced using central composite design and desirability function. Under optimized conditions, the linear range 0.50-5.00 µg/ mL with R2 = 0.9886, limit of detection 0.341 µg/ mL, limit of quantitation 1.026 µg/ mL. The method showed a relative standard deviation (RSD) of 1.16% for 7 replicate measurements. Preconcentration and Enrichment factors were determined to be 20 and 35 respectively, indicating the method’s efficiency in enhancing fast green detection. The proposed method was applied in real samples successfully.

Abstract The central nervous system (CNS) is one of the primary targets of alcohol-induced damage. Chronic alcohol consumption leads to cognitive deficits, motor impairments, anxiety-like behaviors, and even irreversible neuronal degeneration and death. However, therapeutic strategies for alcohol-related neurotoxicity remain limited, posing a significant public health concern. Ursolic acid (UA), with its antioxidant, anticancer, anti-inflammatory, hepatoprotective, and immunomodulatory properties, may confer protective effects against neurological damage. In this study, we established a zebrafish model of alcohol-induced neurotoxicity and investigated the potential of UA to mitigate neural injury. Using confocal live imaging in transgenic zebrafish lines, we observed that UA significantly alleviated alcohol-induced reductions in neuronal and dopaminergic neuron populations. Behavioral assays further demonstrated that UA restored normal locomotor activity in zebrafish embryos, indicating functional recovery of the nervous system. Transcriptomic sequencing revealed that UA ameliorated alcohol-induced neurotoxicity potentially by modulating the MAPK signaling pathway and promoting extracellular matrix (ECM) remodeling. This study provides experimental evidence for UA as a therapeutic candidate against alcohol-related neural damage and identifies potential molecular targets for clinical interventions.

Abstract The management of marine dredged sediments is a critical environmental and economic issue, particularly in port cities where dredging is a necessary activity to maintain navigability. These sediments are typically viewed as waste products and often require costly and environmentally challenging disposal methods. However, repurposing dredged sediments as a component in concrete production presents a promising solution for both waste management and the creation of sustainable construction materials. Despite this potential, determining the optimal percentage of sediment incorporation and accurately predicting the mechanical properties, such as compressive strength, remain significant challenges. This study proposes an artificial intelligence (AI)-based approach to predict the optimal incorporation percentage of marine dredged sediments from Moroccan ports into concrete and to forecast the resulting compressive strength. A dataset consisting of 104 samples, including dune sand and port sediments from JEBHA, was used. The data includes key properties such as granulometry, cleanliness, fineness modulus, and the compressive strength of the concrete mixtures. These experimental data were employed to train and validate several machine learning models, including linear regression, Random Forest, Gradient Boosting, and XGBoost, chosen for their ability to model complex, non-linear relationships between sediment characteristics and concrete performance. The performance of these models was evaluated using two key metrics: the coefficient of determination (R²) and the root mean square error (RMSE). Among the models tested, the Random Forest Regressor delivered the best results, with an R² value greater than 0.98 and an RMSE of less than 0.20 MPa, indicating highly accurate predictions of both the optimal sediment incorporation rate and the compressive strength of the concrete. This model’s exceptional performance underscores its potential as a reliable tool for optimizing the use of dredged sediments in concrete production. The findings of this study demonstrate the considerable potential of AI in optimizing the incorporation of marine dredged sediments into concrete. By accurately predicting the mechanical properties of the resulting material, this approach enables the development of more sustainable construction practices while reducing the environmental burden associated with sediment disposal. Moreover, this work illustrates the broader applicability of AI in addressing environmental challenges, offering a pathway to valorize waste materials in the construction industry. The study not only advances our understanding of sediment utilization in concrete but also contributes to the growing field of sustainable material science, offering promising avenues for future research and development. Nevertheless, further research is needed to validate the model’s scalability to other sediment types and assess practical limitations in industrial applications.

Abstract The increase in global energy consumption is paralleled by an increase in the waste generated from it, especially those related to used batteries which constitute a source of contamination of the environment and a great attaint for the human health. Therefore, it has become more necessary to work on recycling batteries to revalue their active materials and to preserve the environment. The aim of this work was the synthesis and characterization of nanostructured PbO obtained from spent lead acid batteries negative plate. The negative plates of used battery are made up of large amounts of PbSO4 and smaller amounts of Pb. The PbSO 4  was desulfated with (NH 4 ) 2 CO 3  to obtain PbCO 3  which is then calcined in air at different temperatures.in this work we are interested in studying the effect of temperature on the nature and the morphology of the products of the calcination process. The results show that at a 450°c we obtain α-PbO, at 500°c β-PbO, after these temperature we get a mixture of lead oxides α-PbO, β-PbO, and minium Pb 3 O 4 . α-PbO granules have sizes around 26 nm with a mesoporous materials and BET surface area was equal to about 4 m 2 /g.

Abstract Heterocyclic compounds, characterized by rings containing non-carbon atoms like nitrogen, oxygen, or sulfur, are fundamental in diverse fields. This review provides an overview of heterocyclic chemistry, with a focused examination of benzimidazoles. It covers their structure, chemical properties, synthetic methods (including classical and modern techniques emphasizing efficiency and sustainability), and broad therapeutic applications across various disease areas, highlighting their significance in drug development and materials science. From (2018-2024)