Moulay Ismail University

This study developed a sustainable and recyclable photocatalytic system for wastewater treatment based on green-synthesized ZnO nanoparticles using Argania spinosa press-cake extract. The ZnO nanoparticles were statistically optimized through a Box–Behnken design, achieving a maximum BET surface area of 20.109 m2 g−1, and were subsequently incorporated into binary (CS@ZnO) and ternary (CS@ZnO@Ghassoul) nanocomposite beads.The ternary nanocomposite exhibited the highest BET surface area (39.823 m2 g−1), surpassing those of CS@ZnO (31.145 m2 g−1) and the green-synthesized ZnO nanoparticles (20.109 m2 g−1). Under UV-A irradiation, CS@ZnO@Ghassoul achieved 97.87% degradation of Basic Yellow 28 within 40 min, with an apparent reaction rate constant (kapp) of 0.1071 min−1, while maintaining degradation efficiencies above 96% after three regeneration cycles. Radical scavenging experiments identified hydroxyl radicals (•OH) as the predominant reactive species. Density functional theory (DFT) calculations supported the experimental findings, revealing that Basic Yellow 28 possesses a narrow energy gap (2.05 eV), indicating high reactivity. The high electrophilicity index (ω = 4.59 eV) confirms that BY28 is a strong electron acceptor, readily attracting electrons from the photocatalyst surface. Additionally, the high charge transfer capacity (ΔNmax = 2.92) demonstrates its strong ability to exchange electrons with ZnO, thereby facilitating rapid oxidative degradation. Furthermore, the regenerated CS@ZnO@Ghassoul beads removed 99.5% of Cu2+ within 110 min and successfully treated real textile wastewater, reducing chemical oxygen demand, biochemical oxygen demand, and dye content by 97.3%, 67.0%, and 59.9%, respectively.Overall, these findings demonstrate that the CS@ZnO@Ghassoul nanocomposite is an efficient, reusable, and environmentally friendly material for sustainable wastewater remediation.

Background The textile industry generates substantial volumes of dye-contaminated wastewater, posing severe environmental and health risks due to the persistence, toxicity, and resistance to biodegradation of synthetic dyes such as Crystal Violet (CV) and Methylene Violet (MV). This study aimed to develop a sustainable and efficient nanocomposite adsorbent by combining green-synthesized titanium dioxide (TiO₂) nanoparticles with chitosan (CS) to address the limitations of conventional dye removal methods, including high cost, energy consumption, and generation of harmful by-products. Methods TiO₂ nanoparticles were synthesized via a green route using crude aqueous ginger extract, with synthesis optimized by a Box–Behnken design considering extract volume (1–5 mL), titanium precursor concentration (0.1–0.5 M), and calcination temperature (400–500°C). The optimized TiO₂ nanoparticles were immobilized in chitosan beads to fabricate the CS@TiO₂ nanocomposite. The material was characterized by FTIR, XRD, SEM-EDS, BET, and pHPZC analyses. Adsorption performance was evaluated through kinetic, isotherm, thermodynamic, reusability, and DFT studies, and validated using real textile wastewater. Findings The optimal conditions (5 mL CAE, 0.3 M precursor, 400°C) produced mesoporous TiO₂ nanoparticles with a BET surface area of 150.49 m² g⁻¹ and a particle size of 10.38 nm. Chitosan incorporation increased the surface area to 201.24 m² g⁻¹ with an average pore diameter of 8.25 nm. CS@TiO₂ reached adsorption equilibrium within 120 min, following pseudo-second-order kinetics (R²=0.992 for CV and 0.989 for MV) and the Langmuir model, with maximum capacities of 165.84 mg g⁻¹ for CV and 132.84 mg g⁻¹ for MV. Adsorption was spontaneous and endothermic, with ΔG° values of −6.26 to −7.84 kJ mol⁻¹ for CV and −3.86 to −4.59 kJ mol⁻¹ for MV. DFT showed a reduction in the HOMO–LUMO gap from 5.27 to 1.20 eV, while CV exhibited higher global softness (1.65 eV⁻¹) than MV (0.26 eV⁻¹). In real textile wastewater, the nanocomposite removed 87.75% COD, 75.00% BOD₅, and 98.35% electrical conductivity, with near-complete decolorization, and retained 67.77% CV removal after five cycles, confirming its potential as an efficient and reusable adsorbent.

Packed bed latent heat storage systems using phase change materials enable efficient thermal energy storage and recovery, motivating investigation of their coupled flow and heat transfer behavior during charging. This study develops a theoretical and numerical model of an axisymmetric storage tank filled with paraffin and traversed by downward hot-water flow to analyze system dynamics under realistic conditions. Transient momentum and heat transport were solved using a finite element approach with separate energy equations for the heat transfer fluid and storage medium, and the model was validated against experimental data with good agreement. Simulations conducted at a mass flow rate of 0.2 L/min, inlet temperature of 90 °C, and porosity of 0.49 show that fluid velocity decreases markedly inside the porous region by 93.75% (compared to the clear region) due to pressure losses and viscous resistance, resulting in the successful maintenance of a sharp and highly stratified thermocline front along the bed. Thermal results indicate faster temperature diffusion in the fluid than in the phase change material, producing distinct thermocline thicknesses. Melting onset and duration vary along the tank height, occurring earlier near the inlet and later downstream. The local liquid fraction follows the temperature distribution of the storage medium, rising significantly at each level until it reaches 52%, after which it increases slowly by about 2% before the tank reaches full saturation (θ2 = 100%) within a reasonable time. These findings clarify the interplay between flow resistance, heat transfer, and phase change, providing quantitative insight for design and optimization of packed bed thermal storage systems.

In recent years, the reduction of carbon emissions has led to the integration of renewable energies into electricity grids. This has improved their distributed structure. However, this transformation has also increased the attack surface. Traditionally, cybersecurity is addressed through standard methods and predictable solutions. These often neglect the inherent fluctuation of renewable energies. From a resilience perspective, the smart grid must function as a cyber-physical ecosystem. Availability and responsiveness are paramount, as cyberattacks against these infrastructures can rapidly lead to instability. They require unified detection, mitigation, and recovery (DMR) strategies. Combined approaches, leveraging physical knowledge and data-centric models, offer a greater capacity to detect discrete threats specific to renewable energies. This paper provides a critical assessment. It examines the maturity and practical relevance of new DMR approaches for smart grids powered by renewable energies. It highlights the strengths and limitations of the work analyzed. Thus, digital twins enable the testing of mitigation strategies, blockchain strengthens trust in transactions, and robust microarchitectures underpin effective recovery. Nevertheless, major challenges persist regarding scalability, interoperability, and real-time response capabilities. This article therefore proposes: (a) a unified conceptual framework; (b) an integrated security checklist; and (c) a research roadmap for securing critical energy infrastructures. These frameworks promote the comprehensive and secure integration of DMR technologies and ensure their scalability, compatibility, and effectiveness in addressing emerging cyber risks.

This study investigates the determinants shaping Moroccan companies' intention to adopt the International Sustainability Standards Board (ISSB) reporting framework, illuminating how cultural, ethical, and organizational factors converge in shaping sustainability practices in an emerging market. Grounded in the diffusion of innovations (DoI) theory, the research examines the roles of religiosity, perceived cost, perceived risk, and relative advantage, with organizational readiness conceptualized as a pivotal mediating construct. Drawing on data from 303 Moroccan accounting professionals, the study employs a dual structural equation modeling (SEM) approach-covariance based for model specification and partial least squares for structural testing-to ensure analytical robustness. The results reveal that religiosity and relative advantage exert direct and significant effects on adoption intention, while perceived cost and perceived risk influence adoption indirectly through organizational readiness. Notably, perceived cost emerges as the strongest driver of readiness, reframing financial investment as a pathway rather than a barrier to sustainable transformation. Beyond its empirical contributions, the study underscores the ethical and spiritual dimensions of sustainability, suggesting that religiosity-particularly within Islamic contexts-can act as a moral catalyst for environmental stewardship. By highlighting readiness as the linchpin connecting belief systems, economic considerations, and institutional behavior, the research enriches contemporary debates on sustainability reporting in developing economies and extends the moral discourse surrounding corporate engagement with the ISSB framework.