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Multiscale Modeling of Water Transpo...

Boateng, Linkel Kwabena.

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Multiscale Modeling of Water Transport and the Influence of Water Quality Parameters on Membrane Processes.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Multiscale Modeling of Water Transport and the Influence of Water Quality Parameters on Membrane Processes./
Author:	Boateng, Linkel Kwabena.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
Description:	118 p.
Notes:	Source: Dissertation Abstracts International, Volume: 77-12(E), Section: B.
Contained By:	Dissertation Abstracts International77-12B(E).
Subject:	Civil engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10126932
ISBN:	9781339849706

Multiscale Modeling of Water Transport and the Influence of Water Quality Parameters on Membrane Processes.
Boateng, Linkel Kwabena.

Multiscale Modeling of Water Transport and the Influence of Water Quality Parameters on Membrane Processes. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 118 p.

Source: Dissertation Abstracts International, Volume: 77-12(E), Section: B.

Thesis (Ph.D.)--University of South Carolina, 2016.

Membrane-based desalination processes have become a viable means of producing potable water to meet water resource needs in both industrialized and developing nations. Extensive experimental investigation, in conjunction with computational modeling is critical in the development of sustainable and cost-effective desalination technologies. The overall goal of this dissertation is to develop a multiscale modeling framework to elucidate water and salt transport mechanisms and the influence of water quality parameters on membrane processes. The key tasks involved in this study are: establish a criterion for estimating water flux using Bayesian inference; develop a multiscale framework to connect molecular dynamics (MD) simulations to the process level; and evaluate the influence of different water chemistry conditions on water flux in forward and reverse osmosis membrane processes. Simulations are conducted to evaluate water transport and natural organic matter (NOM) fouling propensity in cellulose-triacetate (CTA) and nanoporous graphene (NPG) membranes. Bayesian updating of a probabilistic model is performed to estimate membrane permeability and a process model is developed to predict full-scale water flux through the membrane. Results of the Bayesian inference indicate that the use of unique structural configurations in MD simulations is essential to capture realistic membrane properties at the molecular scale. Full-scale water flux predictions based on estimated membrane parameters is within the same order of magnitude of experimental data suggesting that simulations at the molecular level can potentially be scaled up to reflect process level conditions. Moreover, surface functionalization of NPG membranes can enhance water flux and salt rejection and improve antifouling capabilities. NOM adsorption onto NPG membrane is energetically favored and results in water flux decline across the membrane due to increased resistance to flow. The results further indicate that fouling propensity of graphene-based membranes is influenced by surface functionalization which dictates the strength of the interactions between the membranes and potential foulants. This work highlights the feasibility of forward osmosis processes and the potential application of ultrathin graphene membranes for water desalination. The findings can complement experimental studies to better understand observations at the macro-scale and expedite the development of mechanistic strategies for optimizing membrane performance.

ISBN: 9781339849706Subjects--Topical Terms:

860360
Civil engineering.

Multiscale Modeling of Water Transport and the Influence of Water Quality Parameters on Membrane Processes.
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502 $a Thesis (Ph.D.)--University of South Carolina, 2016.
520 $a Membrane-based desalination processes have become a viable means of producing potable water to meet water resource needs in both industrialized and developing nations. Extensive experimental investigation, in conjunction with computational modeling is critical in the development of sustainable and cost-effective desalination technologies. The overall goal of this dissertation is to develop a multiscale modeling framework to elucidate water and salt transport mechanisms and the influence of water quality parameters on membrane processes. The key tasks involved in this study are: establish a criterion for estimating water flux using Bayesian inference; develop a multiscale framework to connect molecular dynamics (MD) simulations to the process level; and evaluate the influence of different water chemistry conditions on water flux in forward and reverse osmosis membrane processes. Simulations are conducted to evaluate water transport and natural organic matter (NOM) fouling propensity in cellulose-triacetate (CTA) and nanoporous graphene (NPG) membranes. Bayesian updating of a probabilistic model is performed to estimate membrane permeability and a process model is developed to predict full-scale water flux through the membrane. Results of the Bayesian inference indicate that the use of unique structural configurations in MD simulations is essential to capture realistic membrane properties at the molecular scale. Full-scale water flux predictions based on estimated membrane parameters is within the same order of magnitude of experimental data suggesting that simulations at the molecular level can potentially be scaled up to reflect process level conditions. Moreover, surface functionalization of NPG membranes can enhance water flux and salt rejection and improve antifouling capabilities. NOM adsorption onto NPG membrane is energetically favored and results in water flux decline across the membrane due to increased resistance to flow. The results further indicate that fouling propensity of graphene-based membranes is influenced by surface functionalization which dictates the strength of the interactions between the membranes and potential foulants. This work highlights the feasibility of forward osmosis processes and the potential application of ultrathin graphene membranes for water desalination. The findings can complement experimental studies to better understand observations at the macro-scale and expedite the development of mechanistic strategies for optimizing membrane performance.
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