Designing durable self-cleaning nanofiltration membranes via sol-gel assisted interfacial polymerization for textile wastewater treatment

Construction of Mineralization Nanostructures in Polymers for Mechanical Enhancement and Functionalization

Mineralization capable of growing inorganic nanostructures efficiently, orderly, and spontaneously shows great potential for application in the construction of high-performance organic-inorganic composites. As a thermodynamically spontaneous solid-phase crystallization reaction involving dual organic and inorganic components, mineralization allows for the self-assembly of sophisticated and exclusive nanostructures within a polymer matrix. It results in a diversity of functions such as enhanced strength, toughness, electrical conductivity, selective permeability, and biocompatibility. While there are previous reviews discussing the progress of mineralization reactions, many of them overlook the significant benefits of interfacial regulation and functionalization that come from the incorporation of mineralized structures into polymers. Focusing on different means of assembly of mineralized nanostructures in polymer, the work analyzes their design principles and implementation strategies. Then, their different advantages and disadvantages are analyzed by combining nanostructures with organic substrates as well as involving the basis of different functionalizations. It is anticipated to provide insights and guidance for the future development of mineralized polymer composites and their application designs.

Quantification of interfacial interaction related with adhesive membrane fouling by genetic algorithm back propagation (GABP) neural network

Since adhesive membrane fouling is critically determined by the interfacial interaction between a foulant and a rough membrane surface, efficient quantification of the interfacial interaction is critically important for adhesive membrane fouling mitigation. As a current available method, the advanced extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory involves complicated rigorous thermodynamic equations and massive amounts of computation, restricting its application. To solve this problem, artificial intelligence (AI) visualization technology was used to analyze the existing literature, and the genetic algorithm back propagation (GABP) artificial neural network (ANN) was employed to simplify thermodynamic calculation. The results showed that GABP ANN with 5 neurons could obtain reliable prediction performance in seconds, versus several hours or even days time-consuming by the advanced XDLVO theory. Moreover, the regression coefficient (R) of GABP reached 0.9999, and the error between the prediction results and the simulation results was less than 0.01%, indicating feasibility of the GABP ANN technique for quantification of interfacial interaction related with adhesive membrane fouling. This work provided a novel strategy to efficiently optimize the thermodynamic prediction of adhesive membrane fouling, beneficial for better understanding and control of adhesive membrane fouling.

Enhancing the Antifouling Ability of a Polyamide Nanofiltration Membrane by Narrowing the Pore Size Distribution via One-Step Multiple Interfacial Polymerization

Application of nanofiltration membranes in industries still has to contend with membrane fouling that causes a significant loss of separation performance. Herein, an innovative approach to design antifouling membranes with a narrowed pore size distribution by interfacial polymerization (IP) assisted by silane coupling agents is reported. An aqueous solution of piperazine anhydrous (PIP) and γ-(2,3-epoxypropoxy) propytrimethoxysilane (KH560) is employed to perform IP with an organic solution of trimesoyl chloride and tetraethyl orthosilicate (TEOS) on a porous support. In accordance with the results of molecular dynamics and dissipative particle dynamics simulations, the reactive additive KH560 accelerates the diffusion rate of PIP to enrich at the reaction boundary. Moreover, the hydrolysis/condensation of KH560 and TEOS at the aqueous/organic interface forms an interpenetrating network with the polyamide network, which regulates the separation layer structure. The characterization results indicate that the polyamide-silica membrane has a denser, thicker, and uniform separation layer. The mean pore size of the polyamide-silica membrane and the traditional polyamide membrane is 0.62 and 0.74 nm, respectively, and these correspond to the geometric standard deviation (namely, pore size distribution) of 1.39 and 1.97, respectively. It is proved that the narrower pore size distribution endows the polyamide-silica membrane with stronger antifouling performance (flux decay ratio decreases from 18.4 to 3.8%). Such a membrane also has impressive long-term antifouling stability during cane molasses decolorization at a high temperature (50 °C). The outcomes of this study not only provide a novel one-step multiple IP strategy to prepare antifouling nanofiltration membranes but also emphasize the importance of pore size distribution in fouling control for various industrial liquid separations.

A Novel BiOCl Based Nanocomposite Membrane for Water Desalination

In this study, BiOCl based nanocomposites were used as photocatalytic membranes for a simulated study on water desalination in reverse osmosis membrane systems. Through molecular dynamic simulation, the molecular structure of BiOCl, BiOCl/Ag2S and BiOCl/Bi2O3 heterojunctions were designed and their electronic properties, mechanical properties, and membrane performance for water desalination were evaluated for the first time. The molecular structure was created, and a geometry optimization task was used to optimize it. Material Studio 2019 CASTEP was used for simulation of the electronic and mechanical properties and water desalination was performed by ReaxFF software under pressures between 0 and 250 MPa. The novel BiOCl based nanocomposites showed improved electronic and mechanical properties and, most importantly, improvements in salt rejection and water permeability as compared to well-known materials such as graphene and MoS2. BiOCl and BiOCl/Ag2S had a bandgap around two, which is the ideal bandgap for semiconductor photocatalysts. A salt rejection of 98% was achieved under an applied pressure of 10 MPa. Salt rejection was higher for BiOCl/Bi2O3, while water permeability was higher for BiOCl/Ag2S. The monolayer BiOCl was unstable under pressures higher than 50 MPa, but the mechanical stability of BiOCl/Ag2S increased twofold and increased fourfold for BiOCl/Bi2O3, which is even higher than MoS2. However, between the three nanocomposites, BiOCl/Ag2S was found to be the most ideal photocatalytic nanocomposite membrane.