In this work, hydrocyclones with a diameter of 45 mm and cone lengths of 85 mm and 110 mm were employed to investigate the classification behavior of silicon carbide particles. Numerical simulations were carried out using FLUENT based on computational fluid dynamics (CFD). The internal flow characteristics were modeled using the Volume of Fluid (VOF) approach for multiphase flow, coupled with the Large Eddy Simulation (LES) turbulence model. Furthermore, the Discrete Phase Model (DPM) was applied to track particle trajectories and analyze their dynamic behavior within the hydrocyclone. The experimental results showed that, under identical inlet pressure conditions, the hydrocyclone with a cone length of 110 mm achieved superior separation efficiency. Increasing the cone length leads to a reduction in cone angle, which contributes to improved classification performance. However, practical design constraints limit the extent to which the cone length can be increased. To further explore this effect, an extended cone geometry of 150 mm was investigated through numerical simulation. The CFD results indicate that a longer cone structure enhances air core stability, prolongs particle residence time, and decreases the probability of particle misclassification. These findings suggest that optimizing cone length is an effective strategy for improving hydrocyclone performance. The novelty of this study lies in the integration of experimental validation and numerical simulation to systematically evaluate both practical and extended cone designs, thereby providing deeper insights into the relationship between structural parameters and separation efficiency.

Cocoa pod husk (CPH), a major agro-industrial residue, contains valuable bioactive compounds whose recovery can support sustainable waste valorization. This study evaluated the influence of increasing ethanol concentrations on the ultrasound-assisted extraction (UAE) of bioactive compounds from CPH and their antioxidant, antihypertensive, and antihyperglycemic activity. Dried and milled CPH was extracted using ethanol–water mixtures (0–100% ethanol) under fixed ultrasonic conditions. Cocoa pod husk powder characterization and the resulting extracts were analyzed in terms of chemical composition (lignocellulosic compounds, proximate and elemental composition, and bromatological composition), antioxidant capacity, and in vivo antihypertensive and antihyperglycemic effects in Wistar rats. The results showed that solvent polarity strongly modulated extraction efficiency: absolute ethanol yielded the highest phenolic (171.43 mg GAE/g) and flavonoid (132.05 mg QE/g) content, whereas hydroalcoholic mixtures, particularly 50:50, enhanced overall antioxidant performance, especially in FRAP. The chemical analysis results showed the selective recovery of compounds such as quercetin, hesperidin, and theobromine, and FTIR-PCA results revealed distinct solvent-dependent chemical profiles. In vivo assays indicated modest blood pressure stabilization and a more pronounced antihyperglycemic effect after chronic administration. Overall, UAE proved an effective, rapid, and solvent-efficient method for CPH valorization, highlighting its potential for producing natural antioxidants applicable to food, nutraceutical, and cosmetic formulations.

Rotating packed beds (RPBs) have recently attracted significant attention as a promising approach to intensify the performance of traditional packed columns. Although many lab-scale experimental and numerical studies on RPBs are available in the literature, there is a scarcity of operational data for large-scale RPBs. In this research, high gas flow rates in large-scale RPBs are investigated using computational fluid dynamics (CFD) simulation to predict the dry pressure drop in a rotating bed. A 2D geometry with periodic boundary conditions was applied to simulate the turbulent gas flow in a rotating packed bed. The simulation results provide valuable insights into the gas flow dynamics within rotating beds, highlighting the pressure and velocity variations that occur at high rotational speeds. A semi-empirical correlation successfully replicated the results obtained in this study and can be utilized to predict the pressure drop in large-scale RPBs under operating conditions similar to those studied in this research.

The photocatalytic degradation of Crystal Violet (CV) using ZnO-based nanomaterials presents a promising solution for addressing water pollution caused by synthetic dyes. This review highlights the exceptional efficiency of ZnO and its modified forms—such as doped, composite, and heterostructured variants—in degrading CV under both ultraviolet (UV) and solar irradiation. Key advancements include strategic bandgap engineering through doping (e.g., Cd, Mn, Co), innovative heterojunction designs (e.g., n-ZnO/p-Cu2O, g-C3N4/ZnO), and composite formations with graphene oxide, which collectively enhance visible-light absorption and minimize charge recombination. The degradation mechanism, primarily driven by hydroxyl and superoxide radicals, leads to the complete mineralization of CV into non-toxic byproducts. Furthermore, this review emphasizes the emerging role of Artificial Neural Networks (ANNs) as superior tools for optimizing degradation parameters, demonstrating higher predictive accuracy and scalability compared to traditional methods like Response Surface Methodology (RSM). Potential operational challenges and future directions—including machine learning-driven optimization, real-effluent testing potential, and the development of solar-active catalysts—are further discussed. This work not only consolidates recent breakthroughs in ZnO-based photocatalysis but also provides a forward-looking perspective on sustainable wastewater treatment strategies.

The rising dependence on fossil fuels has intensified greenhouse gas emissions, necessitating the development of renewable energy alternatives. Biogas is a sustainable fuel source; however, its low energy density hinders direct commercial application. This study explores the potential of upgrading biogas to biomethane (Bio-CNG) via CO2 methanation, using Aspen Plus v14.0 simulations and techno-economic analysis. Equilibrium studies revealed that optimal conditions of 300–400 °C, 1–5 bar, and a H2/CO2 ratio of 4 achieve CO2 conversion above 99%, methane selectivity exceeding 92%, and near-complete suppression of CO formation. The developed process flowsheet delivered a methane-rich stream (>92% CH4 + H2) with high yield. Economic evaluation showed that at optimal conditions, the process achieves a positive net present value (NPV) of $12.2 million (1 bar) and $1.7 million (5 bar) and a payback period as low as 0.92 years (1 bar) or 5.6 years (5 bar), depending on the pressure scenario. These results demonstrate that biogas upgrading through CO2 methanation is not only technically feasible but also economically competitive, supporting its integration into existing energy systems and contributing to the transition toward renewable fuels.

Conventional wastewater treatment methods typically achieve 70–90% removal efficiency for organic pollutants. However, the global wastewater crisis—with 80% of wastewater discharged untreated—demands innovative solutions to overcome persistent challenges in nutrient removal and resource recovery. This review presents the first systematic analysis of technology integration strategies for algal wastewater treatment, examining synergistic combinations of biofilm reactors, nano-enhancement, artificial intelligence, and 3D printing technologies. Individual technologies demonstrate distinct performance characteristics: algal biofilm reactors achieve 60–90% removal efficiency with biomass productivity up to 50 g/m2/day; nano-enhanced systems reach 70–99% pollutant removal; AI optimization provides 15–35% efficiency improvements with 25–35% energy reductions; and 3D-printed architectures achieve 70–90% removal efficiency. The novel integration framework reveals that technology combinations achieve 85–95% overall efficiency compared to 60–80% for individual approaches. Critical challenges include nanomaterial toxicity (silver nanoparticles effective at 10 mg/L), high costs (U.S. Dollar (USD) 50–300 per m2 for 3D components, USD 1500+ per kg for nanomaterials), and limited technological maturity (TRL 4–5 for AI and 3D printing). Priority development needs include standardized evaluation metrics, comprehensive risk assessment, and economic optimization strategies. The integration framework provides technology selection guidance based on pollutant characteristics and operational constraints, while implementation strategies address regional adaptation requirements. Findings support integrated algal systems’ potential for superior treatment performance and circular economy contributions through resource recovery.

Aluminum is the most used non–ferrous metal. It can be recycled saving several natural resources, but generates large amounts of residues with a complex composition—still containing a valuable amount of aluminum, although also including contaminant compounds. The laboratory-scale valorization of an industrial aluminum residue is here used as a powerful didactic resource in Inorganic and Analytical Chemistry and related fields such as Chemistry, Chemical Engineering, Environmental Engineering, Materials Engineering, and related university degrees, since concepts like acid-base properties (particularly amphoterism), redox reactions, speciation diagrams, or solubility–precipitation concepts are applied. The students are encouraged to look for information on the topic, to teamwork, and to elaborate a well-written laboratory report. At the same time, this laboratory work introduces them to advanced laboratory techniques and to incorporate concepts of Circular Economy and various Sustainable Development Goals, educating the students with respect to the environment. Although focused on University studies, this manuscript also contains excellent ideas for secondary teachers to motivate STEM vocations, particularly for Chemistry and Chemical and Environmental Engineering, and is also ideal for being included in the preparation of future Secondary School teachers.

Crystallization is one of the approximately twenty unit operations and is considered to be among the most important due to the large number of chemical compounds it produces, as well as due to the enormous quantities of these substances being manufactured around the world. This article aims to present a mathematical model for the shortcut design of a cooling crystallization unit consisting of the crystallizer and auxiliary equipment, such as an evaporator with its preheater and condenser, a heat pump that acts as the cooling system of the crystallizer, and a crystallizer pressure regulator modeled as an expansion valve. The model estimates an extensive series of variables, including mass and volume flow rates of the streams, heat duties of each piece of equipment, sizing variables such as heat transfer areas of heat exchangers and volumes of the vessels, and product flow rates for each specific feed. It embraces equations for the calculation of a series of stream properties, such as density, specific heat capacity, and latent heat of vaporization. For the sizing of the crystallizer, which is the main equipment of the unit, both flow rates and crystallization kinetics are taken into account. The latter is estimated by experimental data taken in a laboratory crystallizer and includes the crystal’s growth rate as a function of residence time.

The contamination of drinking water by per- and polyfluoroalkyl substances (PFASs) presents a global concern due to their extreme persistence, driven by strong C–F bonds. This study investigated the potential of graphene as a filtration material for PFAS removal, focusing on six key compounds regulated by the U.S. EPA: PFOA, PFNA, GenX, PFBS, PFOS, and PFHxS. Using molecular simulations, adsorption energy, diffusion coefficients, and PFAS-to-graphene distances were analyzed. The results showed that adsorption strength increased with molecular weight; PFOS (500 g/mol) exhibited the strongest adsorption (−171 kcal/mol). Compounds with sulfonic acid head groups (e.g., PFOS) had stronger interactions than those with carboxylate groups (e.g., PFNA), highlighting the importance of head group chemistry. Shorter graphene-to-PFAS distances also aligned with higher adsorption energies. PFOS, for example, had the shortest distance at 8.23 Å (head) and 6.15 Å (tail) from graphene. Diffusion coefficients decreased with increasing molecular weight and carbon chain length, with lower molecules like PFBS (four carbon atoms) diffusing more rapidly than heavier ones like PFOS and PFNA. Interestingly, graphene enhanced PFAS mobility in water, likely by disrupting the water structure and lowering intermolecular resistance. These results highlight graphene’s promise as a high-performance material for PFAS removal and future water purification technologies.

Current work investigates the fabrication and performance of nanocomposite membranes, modified with varying concentrations of hybrid nanostructures comprising titanium nanowires coated with iron nanoparticles (TiO2 NWs-Fe2O3), for the removal of Naphthol Blue Black (NBB) dye from industrial wastewater. A series of analytical tools were employed to confirm the successful modification including scanning electron microscopy and EDX analysis, porosity and hydrophilicity measurements, Fourier-transform infrared spectroscopy, and X-Ray Diffraction. The incorporation of TiO2 NWs-Fe2O3 has enhanced membrane performance significantly by increasing the PWF and improving dye retention rates of nanocomposite membranes. At 0.7 g of nanostructure content, the modified membrane (M8) achieved a PWF of 93 L/m2·h and NBB dye rejection of over 98%. The flux recovery ratio (FRR) analysis disclosed improved antifouling properties, with the M8 membrane demonstrating a 73.4% FRR. This study confirms the potential of TiO2 NWs-Fe2O3-modified membranes in enhancing water treatment processes, offering a promising solution for industrial wastewater treatment. These outstanding results highlight the potential of the novel PES-TiO2 NWs-Fe2O3 membranes for dye removal and present adequate guidance for the modification of membrane physical properties in the field of wastewater treatment.