A theoretical investigation into the effects of functionalized graphene nanosheets on dimethyl sulfoxide separation

Atomistic understanding of Ti3C2 MXene membrane performance for separation of nitrate ions from aqueous solutions

Water desalination, which is a reliable method for providing drinking water and a suitable solution, as well as the membrane filtration method in wastewater treatment, has increased significantly in recent years. In this research, the separation of nitrite and nitrate ions from aqueous solutions was done using the MXene membrane of the Ti3C2 type using molecular dynamics simulation. In this study, various parameters, such as pore size MXene structure, characteristics of cavities, applied pressure, and flux were investigated. To investigate the removal of toxic pollutants from water, water flux, potential mean force, distribution of water molecules, and density were investigated. The results showed that the amount of penetration through the membrane increased with the increase in pressure. It was observed that by applying pressure to the system, the number of water molecules accumulated in front of the membrane decreases because they quickly pass through the membrane, which indicates the positive effect of increasing pressure on the separation rate of molecules. The permeability of this membrane was several times higher than the existing membranes in the industry. So that Mexene membranes, which consist of at least two layers, can repel ions with 100 % success.

Understanding the performance of RHO type zeolite membrane for CH4/N2 separation based on molecular dynamics and deep neural network methods

This study shows a molecular dynamics (MD) simulation study on the performance of the RHO zeolite membrane for separating nitrogen from methane/nitrogen gas mixtures. The contamination of natural gas, predominantly composed of methane, with nitrogen diminishes its value. Zeolite membranes offer promising prospects for gas separation due to their stability, rigid pore structure, and molecular sieving properties. The study investigates the impact of pressure difference (up to 30 MPa), feed composition, and membrane thickness on the separation rate at a system temperature of 298 K. Results demonstrate that the RHO zeolite membrane exhibits high permeability and selectivity for N2 separation, surpassing the upper limit defined by Robson with a maximum permeability of 2.14 × 105 GPU (Gas Permeation Units). Exceptional selectivity of N2 over CH4 molecules is observed. Additionally, altering the feed composition and membrane thickness positively influences the membrane's separation performance, thereby enhancing its efficiency. The findings contribute to the advancement of separation technologies, providing valuable insights into the potential application of zeolite membranes for efficient N2 separation from CH4/N2 gas mixtures in natural gas processing. Furthermore, the study explores the use of Deep Neural Network (DNN) models to predict the membrane's performance under diverse operating conditions. The DNN models, trained using simulation data from MD simulations, exhibit high accuracy with a coefficient of determination (R2) exceeding 0.9, ensuring reliable predictions. The integration of DNN models facilitates the optimization of zeolite membrane-based gas separation systems, improving their design and operation.

A computational investigation of DMSO/water separation through functionalized GO multilayer nanosheet membrane using molecular dynamics simulation and deep neural network model for membrane performance prediction

In this molecular dynamics (MD) simulation study, the separation of dimethyl sulfoxide (DMSO) from water was investigated using multilayer functionalized graphene oxide (GO) membranes. The GO nanosheets were modified with chemical groups (-F, -H) to alter their properties. The study analyzed the influence of pressure and functional groups on the separation rate. Additionally, a deep neural network (DNN) model was developed to predict membrane behavior under different conditions in water treatment processes. Results revealed that the fluorine-functionalized membrane exhibited higher permeation compared to the hydrogen-functionalized one, with potential of mean force (PMF) analysis indicating higher energy barriers for water molecules passing through the hydrogen-functionalized membrane. The study used density profile, water density map analysis, and radial distribution function (RDF) analysis to understand water and DMSO molecule interactions. The diffusion coefficient of water molecules was also calculated, showing higher diffusion in the fluorine-functionalized system. Overall, the findings suggest that functionalized GO membranes are effective for DMSO-water separation, with the fluorine-functionalized membrane showing superior performance. The DNN model accurately predicts membrane behavior, contributing to the optimization of membrane separation systems.

Natural Solid-State Hydrogel Electrolytes Based on 3D Pure Cotton/Graphene for Supercapacitor Application

A conductive cotton hydrogel with graphene and ions can come into contact with electrodes in solid electrolytes at the molecular level, leading to a more efficient electrochemical process in supercapacitors. The inherently soft nature of cotton mixed with hydrogel provides superior flexibility of the electrolyte, which benefits the devices in gaining high flexibility. Herein, we report on the current progress in solid-state hydrogel electrolytes based on 3D pure cotton/graphene and present an overview of the future direction of research. The ionic conductivity of a complex hydrogel significantly increased by up to 13.9 × 10^-3 S/cm at 25 °C, due to the presence of graphene, which increases ionic conductivity by providing a smooth pathway for the transport of charge carriers and the polymer. Furthermore, the highest specific capacitance of 327 F/g at 3 mV/s was achieved with cyclic voltammetry measurement and a galvanostatic charge-discharge measurement showed a peak value of 385.4 F/g at 100 mA/g current density. Furthermore, an electrochemical analysis demonstrated that a composite cotton/graphene-based hydrogel electrolyte is electrically stable and could be used for the design of next-generation supercapacitors.