The effect of Schiff base network on the separation performance of thin film nanocomposite forward osmosis membranes

Effect of titanium oxide/reduced graphene (TiO2/rGO) addition onto water flux and reverse salt diffusion thin-film nanocomposite forward osmosis membranes

Thin-film nanocomposite (TFN) forward osmosis (FO) membranes have attracted significant attention due to their potential for solving global water scarcity problems. In this study, we investigate the impact of titanium oxide (TiO2) and titanium oxide/reduced graphene (TiO2/rGO) additions on the performance of TFN-FO membranes, specifically focusing on water flux and reverse salt diffusion. Membranes with varying concentrations of TiO2 and TiO2/rGO were fabricated as interfacial polymerizing M-phenylenediamine (MPD) and benzenetricarbonyl tricholoride (TMC) monomers with TiO2 and its reduced graphene composites (TiO2/rGO). The TMC solution was supplemented with TiO2 and its reduced graphene composites (TiO2/rGO) to enhance FO performance and reverse solute flux. All MPD/TMC polyamide membranes are characterized using various techniques such as scanning electron microscopy (SEM), atomic force microscopy (AFM), and contact angle measurements. The results demonstrate that incorporating TiO2/rGO into the membrane thin layer improves water flux and reduces reverse salt diffusion. In contrast to the TFC membrane (10.24 L m-2h-1 and 6.53 g/m2 h), higher water flux and higher reverse solute flux were detected in the case of TiO2and TiO2/rGO-merged TFC skin membranes (18.81 and 24.52 L m-2h-1 and 2.74 and 2.15 g/m2 h, respectively). The effects of TiO2 and TiO2/rGO stacking on the skin membrane and the performance of TiO2 and TiO2/rGO skin membranes have been thoroughly studied. Additionally, being investigated is the impact of draw solution concentration.

On the evaluating membrane flux of forward osmosis systems: Data assessment and advanced intelligent modeling

As an emerging desalination technology, forward osmosis (FO) can potentially become a reliable method to help remedy the current water crisis. Introducing uncomplicated and precise models could help FO systems' optimization. This paper presents the prediction and evaluation of FO systems' membrane flux using various artificial intelligence-based models. Detailed data gathering and cleaning were emphasized because appropriate modeling requires precise inputs. Accumulating data from the original sources, followed by duplicate removal, outlier detection, and feature selection, paved the way to begin modeling. Six models were executed for the prediction task, among which two are tree-based models, two are deep learning models, and two are miscellaneous models. The calculated coefficient of determination (R2 ) of our best model (XGBoost) was 0.992. In conclusion, tree-based models (XGBoost and CatBoost) show more accurate performance than neural networks. Furthermore, in the sensitivity analysis, feed solution (FS) and draw solution (DS) concentrations showed a strong correlation with membrane flux. PRACTITIONER POINTS: The FO membrane flux was predicted using a variety of machine-learning models. Thorough data preprocessing was executed. The XGBoost model showed the best performance, with an R2 of 0.992. Tree-based models outperformed neural networks and other models.

Enhancing Chlorine Resistance and Water Permeability during Forward Osmosis Separation Using Superhydrophilic Materials with Conjugated Systems

Poor resistance to free chlorine severely impairs the service of conventional polyamide (PA) membrane in water treatment. Here we design a series of superhydrophilic aromatic sulfonate materials (ASMs) comprising successively increasing conjugated systems and ionizable groups (ASM-1, ASM-2, ASM-3) to develop a chlorine-resistant membrane via chemical modification. By altering the membrane physicochemical properties and surface structure, ASMs substantially improve the chlorine resistance and water permeability of membrane. With 0.5 M NaCl as the draw solution, all ASMs enhance membrane water fluxes by more than 60% relative to those of the nascent PA membrane in forward osmosis (FO) processes. After exposed to a 1000 ppm sodium hypochlorite solution for 2-8 h, the modified membranes exhibit smaller variations in FO performance than the PA membrane. Having the largest conjugated system and the most sulfonate groups, ASM-3 enables the membrane to sustain a chlorination strength of up to 8000 ppm·h with an insignificant NaCl loss during the FO process, surpassing other recently developed PA membranes in chlorine resistance. These results manifest that the combination of a large conjugated system and ionizable group is key for imbuing membrane with excellent chlorine resistance and water permeability.