Tafila Technical University

A novel non-conjugated aromatic polymer that contains azo-linked moieties of diphenylmethane and 2,5-bis-4-(hydroxyphenyl)-1,4-dimethoxybenzene ((MeO)2AzoPhO) has been obtained. The structure of the polymer is corroborated using IR spectroscopy, 1H, 13C NMR, and CP-MAS NMR spectroscopy. With the use of thermogravimetry, it is shown that the compound is thermally stable up to 150°C. Based on the analysis of the electron spectra, it is established that the band gap width (Eg) of (MeO)2AzoPhO equals 3.0-3.4 eV. This value is higher than Eg for the polymeric analogue with a conjugated linker (≈2.9 eV) and consistent with the size of the electron density delocalization regions.

New poly(fluoro-aryl-thiazole) copolymers were synthesized through polycondensation polymerization between aryl-aldehydes (featuring naphthalene, benzene, thiophene, and biphenyl linkers) and dithiooxamide. The successful formation of the polymers was confirmed using spectroscopic techniques, including 1H and 13C NMR, solid-state 13C NMR (CP-MAS), and FTIR. Incorporating thiazole units into the polymer structure increases the sulfur and nitrogen content within the framework. This modification significantly enhances the polymers' thermal stability, as thermogravimetric analysis demonstrates. Additionally, the polymers show improved efficiency in separating Th(IV) and Al(III) ions from aqueous solutions.

This study employs density functional theory (DFT) to investigate the structural and functional properties of the cubic double perovskite hydrides Ca2LiVH6 and Sr2LiVH6 for hydrogen storage applications. The compounds, crystallizing in the cubic structure, are confirmed to be thermodynamically, mechanically, and dynamically stable. Electronic structure calculations reveal semi-metallic behavior with dominant ionic bonding characterized by significant charge transfer. Analysis of the elastic constants confirms a brittle nature and indicates anisotropic mechanical behavior for Ca2LiVH6, in contrast to the isotropic character of Sr2LiVH6. The compounds also exhibit promising optoelectronic properties, including high ultraviolet absorption and a strong dielectric response. Most notably, the calculated hydrogen storage capacities are significant, with Ca2LiVH6 achieving gravimetric and volumetric capacities of 4.20 wt% and 24.8 kg.H2/m3, respectively, while Sr2LiVH6 demonstrates values of 2.53 wt% and 21.7 kg.H2/m3. These comprehensive results confirm the potential of these cubic perovskite hydrides as candidates for solid-state hydrogen storage.

Advanced Oxidation Processes (AOPs) are pivotal technologies for the effective degradation of a wide variety of organic and inorganic pollutants in water and wastewater treatment. This bibliometric analysis evaluates 481 publications from the Scopus database, covering the period from 2010 to November 2025, to explore research trends and developments in the field. The findings reveal a substantial increase in research output, with an average annual growth rate of 22.7%. China leads in publication count with 192 documents, followed closely by the United States with 64 publications, demonstrating their substantial contributions to AOP research. Prominent institutions include Tongji University and Università Degli Studi Di Salerno, emphasizing the global collaboration among 2335 authors from 158 institutions across 74 countries. Key themes emerging from the analysis include high oxidative efficiency of AOPs, their hybrid applications with biological and adsorption methods, and their adaptability in treating persistent pollutants and emerging contaminants. However, challenges such as high operational costs, hazardous byproduct formation, and reliance on specific water matrix conditions remain significant obstacles. Funding sources, notably the National Natural Science Foundation of China, play a crucial role, supporting numerous studies, while journals like “Water Research,” “Chemical Engineering Journal,” and “Science of the Total Environment” are identified as primary venues for disseminating impactful research. Overall, this study underscores the need for innovative strategies and interdisciplinary collaboration to enhance the efficacy and application of AOP technologies in addressing the growing challenges in water treatment and environmental sustainability.

Covert timing channels (CTC) exploit network resources to establish hidden communication pathways, posing significant risks to data security and policy compliance. Therefore, detecting such hidden and dangerous threats remains one of the security challenges. This paper proposes LinguTimeX, a new framework that combines natural language processing with artificial intelligence, along with explainable Artificial Intelligence (AI) not only to detect CTC but also to provide insights into the decision process. LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely. LinguTimeX demonstrates strong effectiveness in detecting CTC across multiple languages; namely English, Arabic, and Chinese. Specifically, the LSTM and RNN models achieved Fl scores of 90% on the English dataset, 89% on the Arabic dataset, and 88% on the Chinese dataset, showcasing their superior performance and ability to generalize across multiple languages. This highlights their robustness in detecting CTCs within security systems, regardless of the language or cultural context of the data. In contrast, the DeepForest model produced Fl-scores ranging from 86% to 87% across the same datasets, further confirming its effectiveness in CTC detection. Although other algorithms also showed reasonable accuracy, the LSTM and RNN models consistently outperformed them in multilingual settings, suggesting that deep learning models might be better suited for this particular problem.