H2O Absorptivity on a Fully 4-crosslinked Polyacrylamide Membrane via Density Functional Theory and Monte Carlo Calculations for Draw Solution Recovery in Forward Osmosis

College

College of Science

Department/Unit

Physics

Document Type

Conference Proceeding

Source Title

2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2019

Publication Date

11-1-2019

Abstract

© 2019 IEEE. The draw solution recovery process is a necessary step in forward osmosis systems, such as the one being applied in the dewatering of microalgae. Among the many draw solution recovery methods, the stimuli-response regeneration technique emerged to be one of the most promising in terms of energy efficiency. However, a material with an excellent capacity to absorb water would be needed for this type of process. This study investigated the water adsorption properties of 4-crosslinked polyacrylamide membrane (PAM) by means of density functional theory and Monte Carlo calculations for potential application in draw solution recovery. A geometrically optimized, stable, and energy minimized 4-crosslinked PAM model was prepared and allowed to be immersed to different amount of water molecules. The adsorption energies of water molecules on PAM were calculated. Results indicate that water molecules are most likely to be adsorbed on the amide groups of 4-crosslinked PAM. It was shown that the addition of lower number of water molecules had the highest probability of water molecules adsorbing on PAM. It was found that the 4-crosslinked PAM can adsorb a minimum of 75 and a maximum of 145 water molecules. Results of the study would be useful as a guide for the synthesis and further characterization of PAM for draw solution recovery in forward osmosis systems, specifically in microalgae dewatering.

html

Digitial Object Identifier (DOI)

10.1109/HNICEM48295.2019.9072782

Upload File

wf_yes

This document is currently not available here.

Share

COinS