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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/24734
Title: An experimental and computational investigation of poly(Piperazineamide) thin-film composite membrane for salts separation from water using artificial neural network
Authors: Mahadeva R.
Mehta R.
Manik, Gaurav
Bhattacharya A.
Published in: Desalination and Water Treatment
Abstract: From ever-evolving techniques for desalination to wastewater treatment, membranes have been established themselves as front runners. Recent advances in the development of thin-film composite (TFC), membranes have enabled efficient contaminant separation in terms of ions as well as organics to improvise water treatment. In this study, poly(piperazine-amide) based three-layer membrane was developed through interfacial polymerization of piperazine (aq.) and 1,3,5-trimesoyl chloride (hexane) on a base polysulfone layer supported on non-woven polyester fabric. Membrane efficiency, in terms of permeate flux and salt rejection, was evaluated experimentally by separating NaCl/Na2 SO4 from solutions having different salt concentrations (500-20,000 mg/L). The experimental results have been further modeled and simulated using artificial neural network (ANN) trained using efficient algorithms: Levenberg-Marquardt backpropagation (LM-BP), scaled conjugate gradient backpropagation (SCG-BP), and particle swarm optimization (PSO). Modeling performance has been compared using regression coefficient and mean square error. Optimal search of acceleration factors (c1 = 1.75/1.5, c2 = 1.75/2.5), weight of inertia (ω = 0.4), swarm size (10), and nodes (10) exhibited superior performance for PSO-ANN model than LM-BP-ANN and SCG-BP-ANN models to enable efficient modeling of output–input correlations. This combined experimental and computational study paves the way for study and development of next-generation TFC membrane materials for desalination and inherent process optimization. © 2021 Desalination Publications. All rights reserved.
Citation: Desalination and Water Treatment, 224: 106-121
URI: https://doi.org/10.5004/dwt.2021.27184
http://repository.iitr.ac.in/handle/123456789/24734
Issue Date: 2021
Publisher: Desalination Publications
Keywords: Artificial neural network
Modeling and simulation
Particle swarm optimization
Poly(piperazine-amide) thin-film composite membrane
Separation of salts
ISSN: 19443994
Author Scopus IDs: 57204158068
56459506400
56595314900
7402635330
Author Affiliations: Mahadeva, R., Department of Polymer and Process Engineering, Indian Institute of Technology, Roorkee, Uttarakhand, India
Mehta, R., Membrane Science and Separation Technology Division, Central Salt and Marine Chemicals Research Institute, Bhavnagar, Gujarat, India
Manik, G., Department of Polymer and Process Engineering, Indian Institute of Technology, Roorkee, Uttarakhand, India
Bhattacharya, A., Membrane Science and Separation Technology Division, Central Salt and Marine Chemicals Research Institute, Bhavnagar, Gujarat, India
Funding Details: The first author would like to thank the Ministry of Human Resource Development (MHRD), Government of India for providing research scholarship for executing the research work and also to Membrane Science and Separation Technology Division, Central Salt and Marine Chemicals Research Institute Bhavnagar, Gujarat, India for offering help with the experimental setup. Ministry of Human Resource Development, MHRD
Corresponding Author: Manik, G.; Department of Polymer and Process Engineering, India; email: gaurav.manik@pe.iitr.ac.in Bhattacharya, A.; Membrane Science and Separation Technology Division, India; email: amit@csmcri.res.in
Appears in Collections:Journal Publications [PE]

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