Mass Transport through Nanostructured Membranes: Towards a Predictive Tool

Darvishmanesh, Siavash; Bruggen, Bart Van der

doi:10.3390/membranes6040049

Cited by 9 publications

(5 citation statements)

References 49 publications

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“…Nowadays, membranes developed for such challenging applications are called solvent-tolerant nanofiltration (STNF) membranes. 2,4 The most common materials used to prepare STNF membranes are polymers, such as polyamide−imides, 5 polydimethylsiloxanes, 6 etc. These polymeric membranes have generally shown high permeability and stable rejection with polar organic solvents such as alcohols or tetrahydrofuran.…”

Section: ■ Introductionmentioning

confidence: 99%

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Controlled Nanoconfinement of Polyimide Networks in Mesoporous γ-Alumina Membranes for the Molecular Separation of Organic Dyes

Kyriakou

Winnubst

Drobek

et al. 2021

ACS Appl. Nano Mater.

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Polyimide networks are key in the development of stable, resilient, and efficient membranes for separation applications under demanding conditions. To this aim, the controlled design of the network's nanostructure and its properties are needed. However, such control remains a challenge with currently available synthesis methods. Here, we present a simple nanofabrication approach that allows the controlled nanoconfinement, growth, and covalent attachment of polyimide (PI) networks inside the mesopores of γ-alumina layers. The attachment of the PI network on the γ-alumina layer was initiated via different prefunctionalization steps that play a pivotal role in inducing the in situ polymerization reaction at the pore entrance and/or at the inner pore surface. The nanoconfinement was found to be limited to the 1.5 μm-thick γalumina supporting layer at maximum, and the resulting hybrid PI/ceramic membranes showed stable performance in a variety of solvents. These PI/ceramic membranes were found to be very efficient in the challenging separation of small organic dye molecules such as Rhodamine B (479 g mol −1 ) from toxic solvents such as dimethylformamide or dioxane. Therefore, this technique opens up possibilities for a multitude of separations. Moreover, the PI synthesis approach can be applied to other applications that also rely on porosity and stability control, such as for advanced insulation and anticorrosion.

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Section: ■ Introductionmentioning

confidence: 99%

“…The most common materials used to prepare STNF membranes are polymers, such as polyamide–imides, polydimethylsiloxanes, etc. These polymeric membranes have generally shown high permeability and stable rejection with polar organic solvents such as alcohols or tetrahydrofuran.…”

Section: Introductionmentioning

confidence: 99%

Controlled Nanoconfinement of Polyimide Networks in Mesoporous γ-Alumina Membranes for the Molecular Separation of Organic Dyes

Kyriakou

Winnubst

Drobek

et al. 2021

ACS Appl. Nano Mater.

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“…In a slightly larger number of works, the Hagen-Poiseuille equation was mentioned 10,11,29,43,52,54 . According to Kong et al 52 , this equation can be written in the form (m 3 /(m 2 •s)):…”

Section: Pore Modelsmentioning

confidence: 99%

Mathematical Simulation of Nanofiltration Process: State of Art Review

Huliienko,

Kornienko,

Muzyka

et al. 2024

ChChT

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A review of publications devoted to the mathematical simulation of the nanofiltration process was carried out, the advantages, limitations, and areas of application of various modeling approaches were determined. It was found that the most effective approaches are based on the extended Nernst-Planck equation, Donnan equilibrium, as well as methods of computational fluid dynamics and molecular dynamics. The use of software for solving nanofiltration simulation problems was considered.

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“…Mathematical descriptions of transport in complex separation membranes are a powerful way to understand mechanisms and formulate design principles. − In dense homogeneous membranes, the solution–diffusion model can extract diffusion and partition coefficients and has successfully predicted solute transport rates . Analogously, pore-flow models yield predictions of diffusion coefficients and solute transport rates in nanoporous membranes .…”

Section: Introductionmentioning

confidence: 99%

Capturing Subdiffusive Solute Dynamics and Predicting Selectivity in Nanoscale Pores with Time Series Modeling

Coscia

Shirts

2020

J. Chem. Theory Comput.

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Fitting mathematical models with a direct connection to experimental observables to the outputs of molecular simulations can be a powerful tool for extracting important physical information from them. In this study, we present two new approaches that use stochastic time series modeling to predict long-time-scale behavior and macroscopic properties from molecular simulation, which can be generalized to other molecular systems where complex diffusion occurs. In our previous work, we studied long molecular dynamics (MD) simulation trajectories of a cross-linked H II phase lyotropic liquid crystal (LLC) membrane, where we observed subdiffusive solute transport behavior characterized by intermittent hops separated by periods of entrapment. In this work, we use our models to parameterize the behavior of the same systems, so we can generate characteristic trajectory realizations that can be used to predict solute mean-squared displacements (MSDs), solute flux, and solute selectivity in macroscopic length pores. First, using anomalous diffusion theory, we show how solute dynamics can be modeled as a fractional diffusion process subordinate to a continuous time random walk. From the MD simulations, we parameterize the distribution of dwell times, hop lengths between dwells, and correlation between hops. We explore two variations of the anomalous diffusion modeling approach. The first variation applies a single set of parameters to the solute displacements and the second applies two sets of parameters based on the solute's radial distance from the closest pore center. Next, we present an approach that generalizes Markov state models, treating the configurational states of the system as a Markov process where each state has distinct transport properties. For each state and transition between states, we parameterize the distribution and temporal correlation structure of positional fluctuations as a means of characterization and to allow us to predict solute MSDs. We show that both stochastic models reasonably reproduce the MSDs calculated from MD simulations. However, qualitative differences between MD and Markov state-dependent model-generated trajectories may in some cases limit their usefulness. With these parameterized stochastic models, we demonstrate how one can estimate the flux of a solute across a macroscopic length pore and, based on these quantities, the membrane's selectivity toward each solute. This work therefore helps to connect microscopic, chemically dependent solute motions that do not follow simple diffusive behavior with long-time-scale behavior, in an approach generalizable to many types of molecular systems with complex dynamics.

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Mass Transport through Nanostructured Membranes: Towards a Predictive Tool

Cited by 9 publications

References 49 publications

Controlled Nanoconfinement of Polyimide Networks in Mesoporous γ-Alumina Membranes for the Molecular Separation of Organic Dyes

Controlled Nanoconfinement of Polyimide Networks in Mesoporous γ-Alumina Membranes for the Molecular Separation of Organic Dyes

Mathematical Simulation of Nanofiltration Process: State of Art Review

Capturing Subdiffusive Solute Dynamics and Predicting Selectivity in Nanoscale Pores with Time Series Modeling

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