Bader Shafaqa Al-Anzi

Plunging jets are used in many environmental and industrial applications to enhance mixing and mass transfer Rates. This study investigates the air entrainment characteristics of a Confined Plunging Liquid Jet Reactor incorporated with Annular-Riser (ACPLJR). The effects of downcomer diameter, annular clearance length, flow rate, and jet length on air entrainment ratio were examined for the same operating conditions for both CPLJR and ACPLJR. The results show that the ACPLJR configuration enhances the air entrainment ratio by 45% at a low flow rate of 300 Lh-1 and 29% at a high flow rate of 1166 Lh-1 compared to CPLJR. Optimization of the ACPLJR was achieved by varying the downcomer diameters and clearance lengths, yielding a maximum air entrainment ratio of 1.06 with a downcomer diameter of 2.5 cm, annulus clearance of 35 cm, and a flow rate of 1166 Lh-1. The study reveals that an integrated CPLJR with annular riser (ACPLJR) enhanced the air entrainment ratio which corresponds to greater mass transfer in the liquid The surface and height rise velocities VL and VR exhibited a dependence on jet length and flow rate, showing distinct trends at low and high flow rates, with VL and VR increasing with jet length at low flow rates (400 Lh-1) and smaller percentage changes at high flow rates (1166 Lh-1). A comparative assessment of CPLJR and ACPLJR performance showed that ACPLJR had better performance in terms of air entrainment ratio, highlighting the efficacy of this innovative design

The performance of a tubular solar still in an arid region was evaluated for producing freshwater from various water sources. The water sources fed to the tubular solar still were blowdown from a seawater desalination plant, recovered water from an oil production facility, rejected seawater from a reverse osmosis treatment plant, seawater, and rejected groundwater from a reverse osmosis treatment plant. The TDS for these water sources ranged from 17,210 mg/L for groundwater to 221,710 mg/L for produced water. Compared with other water types, produced water had distinct characteristics: low pH, a petroleum-like odor, and a reddish-brown color. The estimated average production rates were 5.1, 5.9, 6.1, 6.6, and 6.8 L/m²·day for produced water, reverse osmosis-rejected water, desalination plant blowdown, seawater, and reverse osmosis-rejected groundwater. Different TSS designs were examined to determine whether production rates could be improved using tap water. Production increased slightly when a blackened basin, steel mesh, or both were applied as heat-absorption enhancements. Therefore, the tubular solar still without any enhancements was found to be a better option due to its lower cost and simpler design. The composition of the residual salts (65–73%) did not meet the 97% standard set by the FAO. The results of the study are promising for future upscaling projects aimed at enhancing water security in rural areas and arid regions.

Through the integration of ion-selective interfaces into microchannels, micro–nanofluidic systems can realize diverse macroscale functions such as seawater desalination, lithium-magnesium separation, and trace particle enrichment based on ion concentration polarization (ICP). Although ion transport and electrokinetic flow in membrane-embedded microchannels have been extensively studied, the effects of dissociation reactions on spatial variations of pH and electroconvection remain unclear. This study investigates the electrokinetic transport characteristics coupled with dissociation equilibria, including electroosmotic flow, desalination, ion enrichment, and overall pH distribution within the microchannel. The results show that the buffer reactions maintain the ionic balance of the system when high-mobility ions accumulate near the membrane and, by generating co-ions for charge compensation, limit the enrichment of a single ion species so that its concentration remains below the electroneutrality limit. The acid dissociation reaction is significantly accelerated in the Ohmic and limiting current (LC) regimes due to ion enrichment, resulting in a maximum increase of approximately 7.8% in flow velocity. The coupling between the dissociation reactions and the electroosmotic pumping effect extends the pH disturbance from the local region to the entire channel. In strong electrolytes, the upstream pH rises to approximately 8.3, whereas in weak electrolytes, an overall acidification occurs, with the pH decreasing to approximately 6.1. These findings provide theoretical guidance for optimizing desalination efficiency, manipulating electroosmotic pumping, and enriching pH-sensitive particles in microfluidic systems.

Nowadays, there is an increasing interest in the development of novel bioresorbable membranes for Guided Bone Regeneration (GBR), and for this purpose, hydroxyapatite, from different sources, has been tested in combination with chitosan. This work details the production and the characterization of membranes of chitosan reinforced with hydroxyapatite derived from the bone of armoured catfish (Pterygoplichthys spp.), which is a widely available natural resource. The hydroxyapatite was characterized morphologically and chemically after the particles of hydroxyapatite were incorporated into a chitosan matrix. Then, the impact of adding hydroxyapatite particles into a matrix of chitosan on the roughness, mechanical properties, degradation, and cytotoxicity was evaluated. Subsequently, an in vivo test was carried out with the purpose of elucidating its guided bone regeneration activity, where the newly developed chitosan–hydroxyapatite membranes were implanted in rabbits with calvarial bone defects. The membranes of chitosan–hydroxyapatite presented a very rough surface morphology compared to the membranes of chitosan; moreover, the membranes of chitosan–hydroxyapatite showed superior mechanical tensile properties. The Masson’s trichrome staining analysis histologically demonstrated that the membranes of chitosan–hydroxyapatite enhanced the formation of a complete mineralized bone matrix in the calvarial bone defects. Finally, these findings confirm that the bone of armoured catfish (Pterygoplichthys spp.) is a viable, economic, and environmentally friendly source for isolating hydroxyapatite, which, combined with a matrix of chitosan, can be a suitable alternative to develop biocompatible GBR membranes.

This work is an effort to mitigate the existing environmental issues caused by brine discharge from Kuwait’s desalination plants and to find an economical and efficient way of managing reject brine from local desalination plants. Low- and high-resistance membranes (LRMs and HRMs, respectively) were used to produce salt and low-salinity water from brine effluent utilizing an electrodialysis (ED)–evaporator hybrid system. The effect of high current densities of 300, 400, and 500 A/m² and brine flowrates of 450 and 500 L/h on the quality of produced salt and diluate were investigated for LRM and HRM. The recovered salt purity for LRM is up to 90.58%. Results show that the low-resistance membrane (LRM) achieved higher water recovery, energy consumption, desalination rate, operation time and ion removal rate than those of the high-resistance membrane (HRM) under the same operating conditions. The difference in concentration for 300 A/m² between LRM and HRM increased from 0.93% at 10 min to 8.28% at 140 min. The difference in diluate concentration effluent is negligible for both membranes, whereas LRM produced higher concentrate effluent than HRM for all current densities and low flowrate (400 L/h). The maximum difference between LRM and HRM (with LRM achieving higher concentrations) is 10.7% for 400 A/m². The permselectivity of LRM for monovalent cations decreased with current density, whereas the effect on permselectivity for HRM was insignificant for the current density values. The addition of a neutral cell was effective in reducing the buildup of divalent ions on the inner membrane of the cathode side.

A unique NiO-nanoparticle-based electrochemical sensor functionalized with a para-hexanitrocalix[6]arene derivative (p-HNC6/NiO) is developed for the determination of bisphenol S in real samples.

A confined plunging liquid jet reactor (CPLJR) is an unconventional efficient and feasible aerator, mixer and brine dispenser that operates under many operating conditions. Such operating conditions could be challenging, and hence, utilizing prediction models built on machine learning (ML) approaches could be very helpful in giving reliable tools to manage highly non-linear problems related to experimental hydrodynamics such as CPLJRs. CPLJRs are vital in protecting the environment through preserving and sustaining the quality of water resources. In the current study, the effects of the main parameters on the air entrainment rate, Q_a, were investigated experimentally in a confined plunging liquid jet reactor (CPLJR). Various downcomer diameters (D_c), jet lengths (L_j), liquid volumetric flow rates (Qj), nozzle diameters (d_n), and jet velocities (V_j) were used to measure the air entrainment rate, Q_a. The non-linear relationship between the air entrainment ratio and confined plunging jet reactor parameters suggests that applying unconventional regression algorithms to predict the air entrainment ratio is appropriate. In addition to the experimental work, machine learning (ML) algorithms were applied to the confined plunging jet reactor parameters to determine the parameter that predicts Q_a the best. The results obtained from ML showed that K-Nearest Neighbour (KNN) gave the best prediction abilities, the proportion of variance in the Q_a that can be explained by the CPLJR parameter was 90%, the root mean square error (RMSE) = 0.069, and the mean absolute error (MAE) = 0.052. Sensitivity analysis was applied to determine the most effective predictor in predicting Q_a. The Qj and V_j were the most influential among all the input variables. The sensitivity analysis shows that the lasso algorithm can create an effective air entrainment rate model with just two of the most crucial variables, Qj and V_j. The coefficient of determination (R²) was 82%. The present findings support using machine learning algorithms to accurately forecast the CPLJR system’s experimental results.