Ultra-permeable intercalated metal-induced microporous polymer nano-dots rooted smart membrane for environmental remediation

Modeling the CO2 separation capability of poly(4-methyl-1-pentane) membrane modified with different nanoparticles by artificial neural networks

Membranes are a potential technology to reduce energy consumption as well as environmental challenges considering the separation processes. A new class of this technology, namely mixed matrix membrane (MMM) can be fabricated by dispersing solid substances in a polymeric medium. In this way, the poly(4-methyl-1-pentene)-based MMMs have attracted great attention to capturing carbon dioxide (CO2), which is an environmental pollutant with a greenhouse effect. The CO2 permeability in different MMMs constituted of poly(4-methyl-1-pentene) (PMP) and nanoparticles was comprehensively analyzed from the experimental point of view. In addition, a straightforward mathematical model is necessary to compute the CO2 permeability before constructing the related PMP-based separation process. Hence, the current study employs multilayer perceptron artificial neural networks (MLP-ANN) to relate the CO2 permeability in PMP/nanoparticle MMMs to the membrane composition (additive type and dose) and pressure. Accordingly, the effect of these independent variables on CO2 permeability in PMP-based membranes is explored using multiple linear regression analysis. It was figured out that the CO2 permeability has a direct relationship with all independent variables, while the nanoparticle dose is the strongest one. The MLP-ANN structural features have efficiently demonstrated an appealing potential to achieve the highest accurate prediction for CO2 permeability. A two-layer MLP-ANN with the 3-8-1 topology trained by the Bayesian regulation algorithm is identified as the best model for the considered problem. This model simulates 112 experimentally measured CO2 permeability in PMP/ZnO, PMP/Al2O3, PMP/TiO2, and PMP/TiO2-NT with an excellent absolute average relative deviation (AARD) of lower than 5.5%, mean absolute error (MAE) of 6.87 and correlation coefficient (R) of higher than 0.99470. It was found that the mixed matrix membrane constituted of PMP and TiO2-NT (functionalized nanotube with titanium dioxide) is the best medium for CO2 separation.

Preparation of polyvinyl chloride (PVC) membrane blended with acrylamide grafted bentonite for oily water treatment

The current work aims to advance the hydrophilicity, morphology, and antifouling characteristics of polyvinyl chloride (PVC) membranes for oily wastewater separation by incorporating modified bentonite. The surface of bentonite nanoparticles is altered by adopting the "grafting from" method using the surface-initiated atom transfer radical polymerization (SI-ATRP) approach. The PVC-based membrane is first prepared by blending acrylamide grafted bentonite (AAm-g-bentonite). AAm is grafted on bentonite in the presence of 2,2'-Bipyridyl and copper (I) bromide as a catalyst. The modified bentonite nanoparticles are studied using multiple techniques, such as fourier transform infrared spectroscopy (FTIR), thermal gravimetric analysis (TGA), sedimentation tests, field emission scanning electron microscope (FE-SEM), etc. Flat-sheet PVC-based membrane is prepared by blending AAm-g-bentonite using the nonsolvent induced phase separation (NIPS) technique. Different methods, including FE-SEM, FTIR, sedimentation test, contact angle, porosity, antifouling property, and filtration studies of pure and oily water, are used to characterize and determine the performance of mixed-matrix membranes. Membrane performance is improved in the presence of modified bentonite (i.e., AAm-g-bentonite), with the best result achieved at PVC/AAm-g-ben-8 (i.e., 8 wt % of AAm-g-bentonite). Enhanced pure water flux (293.14 Lm^-2h^-1), permeate flux (123.96 Lm^-2h^-1), and oil rejection >93.2% are obtained by the reduced contact angle (49.1°) and improved porosity (71.22%).

Next-generation graphene oxide additives composite membranes for emerging organic micropollutants removal: Separation, adsorption and degradation

In the past two decades, membrane technology has attracted considerable interest as a viable and promising method for water purification. Emerging organic micropollutants (EOMPs) in wastewater have trace, persistent, highly variable quantities and types, develop hazardous intermediates and are diffusible. These primary issues affect EOMPs polluted wastewater on an industrial scale differently than in a lab, challenging membranes-based EOMP removal. Graphene oxide (GO) promises state-of-the-art membrane synthesis technologies and use in EOMPs removal systems due to its superior physicochemical, mechanical, and electrical qualities and high oxygen content. This critical review highlights the recent advancements in the synthesis of next-generation GO membranes with diverse membrane substrates such as ceramic, polyethersulfone (PES), and polyvinylidene fluoride (PVDF). The EOMPs removal efficiencies of GO membranes in filtration, adsorption (incorporated with metal, nanomaterial in biodegradable polymer and biomimetic membranes), and degradation (in catalytic, photo-Fenton, photocatalytic and electrocatalytic membranes) and corresponding removal mechanisms of different EOMPs are also depicted. GO-assisted water treatment strategies were further assessed by various influencing factors, including applied water flow mode and membrane properties (e.g., permeability, hydrophily, mechanical stability, and fouling). GO additive membranes showed better permeability, hydrophilicity, high water flux, and fouling resistance than pristine membranes. Likewise, degradation combined with filtration is two times more effective than alone, while crossflow mode improves the photocatalytic degradation performance of the system. GO integration in polymer membranes enhances their stability, facilitates photocatalytic processes, and gravity-driven GO membranes enable filtration of pollutants at low pressure, making membrane filtration more inexpensive. However, simultaneous removal of multiple contaminants with contrasting characteristics and variable efficiencies in different systems demands further optimization in GO-mediated membranes. This review concludes with identifying future critical research directions to promote research for determining the GO-assisted OMPs removal membrane technology nexus and maximizing this technique for industrial application.

Melanin Treatment Effect of Vacuoles-Zinc Oxide Nanoparticles Combined with Ascorbic Acid

Currently, ascorbic acid (AA) is widely used as a skin whitening material, but, AA, an unstable hydrophilic molecule, cannot penetrate the skin easily, due to the hydrophobic character of the stratum corneum. Therefore, we conjugated AA with hydrated zinc oxide-an inorganic matrix with positive surface charge, to improve the stability of AA. The metal-conjugated-ascorbic acid (ZnAA) was then combined with yeast vacuole through the vacuolar membrane proteins that relate to metal transportation to create an enhanced vacuole that contained ZnAA. The characteristics of vacuole with ZnAA (ZnAA_Vac) were next examined by various tests that included X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), Field emission scanning electron microscopy (FE-SEM), and energy-dispersive X-ray (EDX) analysis. Furthermore, the ability of ZnAA_Vac to degrade melanin was confirmed in both melanoma cell line B16F10, and the artificial human skin MelanoDerm. The results showed that ZnAA_Vac possessed a higher depigmenting effect than the wild-type vacuole or ascorbic acid by reducing 75% of melanin color. Interestingly, ZnAA_Vac was found to be harmless, and did not cause any cytotoxicity to the cells. Overall, ZnAA_Vac is expected to provide a robust, harmless, and effective whitening agent for the skin.