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.

Autor: Alizadeh M; Department of Chemical Engineering, Sahand University of Technology, Tabriz, Iran., Hasanzadeh A; Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran., Ajalli N; Department of Chemical Engineering, Babol Noshiravani University of Technology, Babol, Iran., Azamat J; Department of Chemistry Education, Farhangian University, P.O. Box 14665-889, Tehran, Iran. Electronic address: j.azamat@cfu.ac.ir.
Jazyk: angličtina
Zdroj: Chemosphere [Chemosphere] 2024 Feb; Vol. 349, pp. 140802. Date of Electronic Publication: 2023 Dec 02.
DOI: 10.1016/j.chemosphere.2023.140802
Abstrakt: 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.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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