Bulletin of the American Physical Society
73rd Annual Meeting of the APS Division of Fluid Dynamics
Volume 65, Number 13
Sunday–Tuesday, November 22–24, 2020; Virtual, CT (Chicago time)
Session J16: Nano Flows: Membranes (8:00am - 8:45am CST)Interactive On Demand
|
Hide Abstracts |
|
J16.00001: Elastic, random pore network model for polymer electrolyte membranes Peter Berg, Philippe Nadon We present the first attempt at describing the flow of water and protons through polymer electrolyte membranes (PEM) by use of an elastic pore network model. The main feature of our approach lies in the interplay between fluxes and pore structures, determined by randomized pore properties, the elasticity of the pores, and the liquid pressure distribution across the network. Closed-form solutions of the Poisson-Nernst-Planck-Stokes equations along each bond (pore) are employed and coupled to a swelling model for the pores which are embedded in the elastic PEM backbone. All parameter values are taken from the literature, leaving little room for the fitting of model results to literature values. The resulting nonlinear problem is solved computationally in an efficient manner. More importantly, computed PEM properties at different operating conditions, such as the specific conductivity and the electro-osmotic drag coefficient, compare favourably to values in the literature. In addition, the analysis reveals insights into the nonlinear couplings between transport processes and the structure of the elastic domain which motivates studies of other elastic, nanofluidic systems. [Preview Abstract] |
|
J16.00002: Nanoscale Study of CO2/CH4 Separation through Two-stage Nanoporous Graphene Membranes Naiyer Razmara, Alexsandro Kirch, Daniela Andrade Damasceno, Julio Romano Meneghini, Caetano Rodrigues Miranda During the last decade, various designs have been introduced to separate CH$_{\mathrm{4\thinspace }}$from other components in gas mixtures. The development of effective membranes with high selectivity and permeability is one of the most challenging subjects in carbon capturing and storage. In this context, we investigated the transport and separation of CO$_{\mathrm{2}}$/CH$_{\mathrm{4}}$ binary mixture through a two-stage bilayer nanoporous graphene design. The molecular dynamics technique is applied to investigate the transport properties. Benchmarked forcefields are adopted for modeling the interactions between different molecules. Three boxes are considered as feeding, transferring, and capturing reservoirs. Three configurations of nanoporous graphene membranes are examined, namely, in-line, offset of 10 angstroms, and offset of 20 angstroms. The simulation results indicate that increasing the offset distance leads to a considerable decrease in the number of CH$_{\mathrm{4}}$ molecules in the CO$_{\mathrm{2}}$ capturing reservoir. This study suggests one of the practical designs for the separation of CH$_{\mathrm{4\thinspace }}$with the application in the CO$_{\mathrm{2}}$ abatement industry. [Preview Abstract] |
|
J16.00003: Reasons behind superior water desalination performance of nanoporous MoS$_{\mathrm{2}}$ Zhonglin Cao, Vincent Liu, Amir Barati Farimani Water desalination is one of the most prevailing technologies to solve freshwater scarcity nowadays. Membranes made of two-dimensional (2D) materials such as single-layer MoS$_{\mathrm{2}}$ and Graphene have been demonstrated to be able to significantly increase the water desalination performance. In this work, we made thorough comparison between popular 2D materials including MoS$_{\mathrm{2}}$, MoSe$_{\mathrm{2}}$, Graphene, Boron Nitride, and Phosphorene and conclude that MoS$_{\mathrm{2}}$ constantly performs 20{\%} - 38{\%} better than the others. We further revealed the reasons of the superior performance of MoS$_{\mathrm{2}}$ from the perspective of water dynamics and structure near the membrane/inside the pores, and the energy barrier for water molecules to transport through the pore. [Preview Abstract] |
|
J16.00004: Ozark Nanopore: Highly efficient and selective Graphene Nanopore designed by Artificial Intelligence for water desalination Yuyang Wang, Zhonglin Cao, Amir Barati Farimani Nanoporous Graphene has been proven to be a strong candidate for water desalination applications. Its ultrathin-thickness makes energy-efficient water desalination possible. The geometry of the pore on Graphene membrane plays a significant role in its water desalination performance. In this work, we proposed a nanopore geometry optimization method for Graphene membrane using Deep Reinforcement Learning (DRL). The nanopore designed using DRL looks similar to Ozark lake fractal shape located in Missouri, enabling significant ion rejection while allowing maximum permeation. The Ozark-shaped pore designed by DRL is shown to have 10{\%} higher ion rejection rate compared with circular pores while allowing the same level of water flux. We further discovered that the reason behind high ion rejection of Ozark-shaped Graphene nanopores is that its shape limited the passage of hydrated ions in some regions inside of the pore. [Preview Abstract] |
Follow Us |
Engage
Become an APS Member |
My APS
Renew Membership |
Information for |
About APSThe American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics. |
© 2024 American Physical Society
| All rights reserved | Terms of Use
| Contact Us
Headquarters
1 Physics Ellipse, College Park, MD 20740-3844
(301) 209-3200
Editorial Office
100 Motor Pkwy, Suite 110, Hauppauge, NY 11788
(631) 591-4000
Office of Public Affairs
529 14th St NW, Suite 1050, Washington, D.C. 20045-2001
(202) 662-8700