Influence of Diffusivity and Sorption on Helium and Hydrogen Separations in Hydrocarbon, Silicon, and Fluorocarbon-Based Polymers

Gas transport mechanisms through gas-permeable membranes in microfluidics: A perspective

Gas-permeable membranes (GPMs) and membrane-like micro-/nanostructures offer precise control over the transport of liquids, gases, and small molecules on microchips, which has led to the possibility of diverse applications, such as gas sensors, solution concentrators, and mixture separators. With the escalating demand for GPMs in microfluidics, this Perspective article aims to comprehensively categorize the transport mechanisms of gases through GPMs based on the penetrant type and the transport direction. We also provide a comprehensive review of recent advancements in GPM-integrated microfluidic devices, provide an overview of the fundamental mechanisms underlying gas transport through GPMs, and present future perspectives on the integration of GPMs in microfluidics. Furthermore, we address the current challenges associated with GPMs and GPM-integrated microfluidic devices, taking into consideration the intrinsic material properties and capabilities of GPMs. By tackling these challenges head-on, we believe that our perspectives can catalyze innovative advancements and help meet the evolving demands of microfluidic applications.

Efficient Helium Separation with Two-Dimensional Metal-Organic Framework Fe/Ni-PTC: A Theoretical Study

Helium (He) is one of the indispensable and rare strategic materials for national defense and high-tech industries. However, daunting challenges have to be overcome for the supply shortage of He resources. Benefitted from the wide pore size distribution, sufficient intrinsic porosity, and high specific surface area, metal–organic framework (MOF) materials are prospective candidates for He purification in the membrane-based separation technology. In this work, through first-principles calculations and molecular dynamics (MD) simulations, we studied the permeability and filtration performance of He by the newly synthesized two-dimensional Fe-PTC MOF and its analogue Ni-PTC MOF. We found that both Fe-PTC and Ni-PTC have superior high performance for He separation. The selectivity of He over N₂ was calculated to be ~10¹⁷ for Fe-PTC and ~10¹⁵ for Ni-PTC, respectively, both higher than most of the previously proposed 2D porous membranes. Meanwhile, high He permeance (10⁻⁴~10⁻³ mol s⁻¹ m⁻² Pa⁻¹) can be obtained for the Fe/Ni-PTC MOF for temperatures ranging from 200 to 500 K. Therefore, the present study offers a highly prospective membrane for He separation, which has great potential in industrial application.

Relations Between Dynamic Localization and Solute Diffusion in Polymers

Various public health concerns can arise from the unintended leaching of additives and impurities from polymeric medical devices or food packaging, which is directly related to each solute's diffusivity D. Both experimental and simulation methods can be used to quantify D, but slow diffusion at physiologic temperature in glassy polymers can render these approaches impractical. Here, we investigate a simulation approach with the potential to more rapidly calculate D. Specifically, we examine links between dynamic localization, characterized by the Debye-Waller factor, ⟨u²⟩, and D in a variety of polymer/solute systems using atomistic molecular dynamics (MD) simulations. Using short, high-temperature MD simulations to estimate D at physiologic temperature, we find that the relation ln D ∝ 1/⟨u²⟩ quantitatively predicts D for small solutes and produces an upper-bound estimate of D for larger solutes. Upper-bound estimates are useful in certain contexts, and we compare our results with another approach for determining upper bounds, the Piringer model, to show where each method may be useful. Then, we examine a modified relation where the Debye-Waller factor is rescaled by the mode coupling temperature T_c, which can produce better estimates of D if T_c is carefully chosen. Last, we compare our approach with several other models that relate temperature or localized dynamics with diffusivity. Although each of these approaches can be used to model D across wide temperature ranges using one or more adjustable parameters, none of them are truly predictive in glassy polymers. Further developments are needed to predict the optimal values of the adjustable parameters a priori.

Perfluorodioxolane Polymers for Gas Separation Membrane Applications

Since the discovery of polytetrafluoroethylene (PTFE) in 1938, fluorinated polymers have drawn attention in the chemical and pharmaceutical field, as well as in optical and microelectronics applications. The reasons for this attention are their high thermal and oxidative stability, excellent chemical resistance, superior electrical insulating ability, and optical transmission properties. Despite their unprecedented combination of desirable attributes, PTFE and copolymers of tetrafluoroethylene (TFE) with hexafluoropropylene and perfluoropropylvinylether are crystalline and exhibit poor solubility in solvents, which makes their processability very challenging. Since the 1980s, several classes of solvent-soluble amorphous perfluorinated polymers showing even better optical and gas transport properties were developed and commercialized. Amorphous perfluoropolymers exhibit, however, moderate selectivity in gas and liquid separations. Recently, we have synthesized various new perfluorodioxolane polymers which are amorphous, soluble, chemically and thermally stable, while exhibiting much enhanced selectivity. In this article, we review state-of-the-art and recent progress in these perfluorodioxolane polymers for gas separation membrane applications.

High-efficiency helium separation through an inorganic graphenylene membrane: a theoretical study

Appropriate interactions between an IGP membrane and He molecules result in efficient helium separation.

Computational Screening of Metal⁻Organic Framework Membranes for the Separation of 15 Gas Mixtures

The Monte Carlo and molecular dynamics simulations are employed to screen the separation performance of 6013 computation-ready, experimental metal⁻organic framework membranes (CoRE-MOFMs) for 15 binary gas mixtures. After the univariate analysis, principal component analysis is used to reduce 44 performance metrics of 15 mixtures to a 10-dimension set. Then, four machine learning algorithms (decision tree, random forest, support vector machine, and back propagation neural network) are combined with k times repeated k-fold cross-validation to predict and analyze the relationships between six structural feature descriptors and 10 principal components. Based on the linear correlation value R and the root mean square error predicted by the machine learning algorithm, the random forest algorithm is the most suitable for the prediction of the separation performance of CoRE-MOFMs. One descriptor, pore limiting diameter, possesses the highest weight importance for each principal component index. Finally, the 30 best CoRE-MOFMs for each binary gas mixture are screened out. The high-throughput computational screening and the microanalysis of high-dimensional performance metrics can provide guidance for experimental research through the relationships between the multi-structure variables and multi-performance variables.

Thermodynamic Modeling of Gas Transport in Glassy Polymeric Membranes

Solubility and permeability of gases in glassy polymers have been considered with the aim of illustrating the applicability of thermodynamically-based models for their description and prediction. The solubility isotherms are described by using the nonequilibrium lattice fluid (NELF) (model, already known to be appropriate for nonequilibrium glassy polymers, while the permeability isotherms are described through a general transport model in which diffusivity is the product of a purely kinetic factor, the mobility coefficient, and a thermodynamic factor. The latter is calculated from the NELF model and mobility is considered concentration-dependent through an exponential relationship containing two parameters only. The models are tested explicitly considering solubility and permeability data of various penetrants in three glassy polymers, PSf, PPh and 6FDA-6FpDA, selected as the reference for different behaviors. It is shown that the models are able to calculate the different behaviors observed, and in particular the permeability dependence on upstream pressure, both when it is decreasing as well as when it is increasing, with no need to invoke the onset of additional plasticization phenomena. The correlations found between polymer and penetrant properties with the two parameters of the mobility coefficient also lead to the predictive ability of the transport model.