scholarly journals Machine learning reveals key ion selectivity mechanisms in polymeric membranes with subnanometer pores

2022 ◽  
Vol 8 (2) ◽  
Author(s):  
Cody L. Ritt ◽  
Mingjie Liu ◽  
Tuan Anh Pham ◽  
Razi Epsztein ◽  
Heather J. Kulik ◽  
...  
Keyword(s):  
Machine Learning ◽  
Ion Selectivity ◽  
Molecular Transport ◽  
Polymeric Membranes ◽  
Transport Mechanisms

Machine learning unveils molecular transport mechanisms obscured by entropy-enthalpy compensation in polymeric membranes.

Mechanism of Ion Exclusion by Sub-2nm Carbon Nanotube Membranes

2008 ◽  
Vol 1106 ◽  
Author(s):  
Francesco Fornasiero ◽  
Hyung Gyu Park ◽  
Jason K Holt ◽  
Michael Stadermann ◽  
Costas P Grigoropoulos ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Carbon Nanotube ◽  
Electrostatic Interactions ◽  
Ion Selectivity ◽  
Molecular Transport ◽  
Water Desalination ◽  
Oxygen Plasma Treatment ◽  
Nanotube Membranes ◽  
Ion Exclusion ◽  
Carbon Nanotube Membranes

AbstractCarbon nanotubes offer an outstanding platform for studying molecular transport at nanoscale, and have become promising materials for nanofluidics and membrane technology due to their unique combination of physical, chemical, mechanical, and electronic properties. In particular, both simulations and experiments have proved that fluid flow through carbon nanotubes of nanometer size diameter is exceptionally fast compared to what continuum hydrodynamic theories would predict when applied on this length scale, and also, compared to conventional membranes with pores of similar size, such as zeolites. For a variety of applications such as separation technology, molecular sensing, drug delivery, and biomimetics, selectivity is required together with fast flow. In particular, for water desalination, coupling the enhancement of the water flux with selective ion transport could drastically reduce the cost of brackish and seawater desalting. In this work, we study the ion selectivity of membranes made of aligned double-walled carbon nanotubes with sub-2 nm diameter. Negatively charged groups are introduced at the opening of the carbon nanotubes by oxygen plasma treatment. Reverse osmosis experiments coupled with capillary electrophoresis analysis of permeate and feed show significant anion and cation rejection. Ion exclusion declines by increasing ionic strength (concentration) of the feed and by lowering solution pH; also, the highest rejection is observed for the salts (A=anion, C=cation, z= valence) with the greatest zA/zC ratio. Our results strongly support a Donnan-type rejection mechanism, dominated by electrostatic interactions between fixed membrane charges and mobile ions, while steric and hydrodynamic effects appear to be less important. Comparison with commercial nanofiltration membranes for water softening reveals that our carbon nanotube membranes provides far superior water fluxes for similar ion rejection capabilities.

scholarly journals Discovery of Innovative Polymers for Next-Generation Gas-Separation Membranes using Interpretable Machine Learning

2021 ◽  
Author(s):  
Jason Yang ◽  
Lei Tao ◽  
Jinlong He ◽  
Jeffrey McCutcheon ◽  
Ying Li
Keyword(s):  
Machine Learning ◽  
Polymer Membranes ◽  
Polymeric Membranes ◽  
Gas Separations ◽  
Separation Performance ◽  
High Fidelity ◽  
Environmental Implications ◽  
Separation Membranes ◽  
Gas Separation Membranes ◽  
Dynamics Simulations

Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research on membrane technologies, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine-learning (ML) implementation for the discovery of innovative polymers with ideal separation performance. Specifically, multitask ML models are trained on available experimental data to link polymer chemistry to gas permeabilities of He, H2, O2, N2, CO2, and CH4. We interpret the ML models and extract chemical heuristics for membrane design, through Shapley Additive exPlanations (SHAP) analysis. We then screen over nine million hypothetical polymers through our models and identify thousands of candidates that lie well above current performance upper bounds. Notably, we discover hundreds of never-before-seen ultrapermeable polymer membranes with O2 and CO2 permeability greater than 104 and 105 Barrer, respectively, orders of magnitude higher than currently available polymeric membranes. These hypothetical polymers are capable of overcoming undesirable trade-off relationship between permeability and selectivity, thus significantly expanding the currently limited library of polymer membranes for highly efficient gas separations. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.

scholarly journals Structures, Properties, and Performances—Relationships of Polymeric Membranes for Pervaporative Desalination

Membranes ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 58 ◽  
Author(s):  
Nayan Singha ◽  
Mrinmoy Karmakar ◽  
Pijush Chattopadhyay ◽  
Sagar Roy ◽  
Mousumi Deb ◽  
...  
Keyword(s):  
High Performance ◽  
Wide Spectrum ◽  
Structural Features ◽  
Polymeric Membranes ◽  
Inorganic Membranes ◽  
Transport Mechanisms ◽  
Performance Potential ◽  
Global Demand ◽  
Commercial Applications ◽  
Mass Transport Mechanisms

For the fulfilment of increasing global demand and associated challenges related to the supply of clean-and-safe water, PV has been considered as one of the most attractive and promising areas in desalinating salty-water of varied salinities. In pervaporative desalination, the sustainability, endurance, and structural features of membrane, along with operating parameters, play the dominant roles and impart paramount impact in governing the overall PV efficiency. Indeed, polymeric- and organic-membranes suffer from several drawbacks, including inferior structural stability and durability, whereas the fabrication of purely inorganic membranes is complicated and costly. Therefore, recent development on the high-performance and cost-friendly PV membrane is mostly concentrated on synthesizing composite- and NCP-membranes possessing the advantages of both organic- and inorganic-membranes. This review reflects the insights into the physicochemical properties and fabrication approaches of different classes of PV membranes, especially composite- and NCP-membranes. The mass transport mechanisms interrelated to the specialized structural features have been discussed. Additionally, the performance potential and application prospects of these membranes in a wide spectrum of desalination and wastewater treatment have been elaborated. Finally, the challenges and future perspectives have been identified in developing and scaling up different high-performance membranes suitable for broader commercial applications.

Identification of Molecular Transport Mechanisms in Micro-Porous Hydrotalcite–Silica Membrane

2014 ◽  
Vol 104 (1) ◽  
pp. 133-144 ◽  
Author(s):  
A. D. Wiheeb ◽  
M. A. Ahmad ◽  
M. N. Murat ◽  
J. Kim ◽  
M. R. Othman
Keyword(s):  
Molecular Transport ◽  
Transport Mechanisms ◽  
Silica Membrane

Predicting Methane Diffusivity in Polymeric Membranes by Molecular Dynamics

2015 ◽  
Vol 1119 ◽  
pp. 461-465
Author(s):  
M.K. Hadj-Kali ◽  
A. Bessadok-Jemai ◽  
S. Haider ◽  
Y. Alzeghayer
Keyword(s):  
Molecular Dynamics ◽  
Small Molecules ◽  
Diffusion Coefficients ◽  
Md Simulations ◽  
Polymeric Membranes ◽  
Transport Mechanisms ◽  
Fluid Equation ◽  
Cell Modules ◽  
Dynamics Simulations ◽  
Materials Studio

Diffusion coefficients of methane (CH4) have been obtained by Molecular Dynamics (MD) simulations combined with Einstein fluid equation. Three polymers were considered, namely polyethylene, polypropylene and poly (cis-1,4-butadiene). All calculations were performed by means of Polymer Builder and Amorphous Cell modules within Materials Studio (Accelrys). The obtained diffusivity results are within the range of published results for similar small molecules. Molecular dynamics simulations proved to be a useful tool for understanding the detailed descriptions and transport mechanisms occurring within the material.

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