A novel method for predictions of the gas permeation parameters of polymers on the basis of their chemical structure

Ryzhikh, Victoria; Tsarev, D. A.; Alentiev, A. Yu.; Yampolskii, Yu. P.

doi:10.1016/j.memsci.2015.03.055

Cited by 34 publications

(25 citation statements)

References 46 publications

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“…This is by far the most accurate prediction model for gas permeabilities based on fitted experimental data. Compared with earlier group contribution and bond contribution methods based on a much larger database (R 2 = 0.9), our fingerprinting method showed better prediction performance [32].…”

Section: Model Performancementioning

confidence: 79%

“…The same group descriptors were used by Hasnaoui et al [31] to build artificial neural network model for prediction of polymer permeability, and the results were compared with Park and Paul, Permachor, and Yampolskii's methods. Ryzhikh et al [32] reported a comparison between the correlation used atomic contributions and bond contribution methods for the prediction of the gas transport parameters (permeability [P] and diffusion [D] coefficients) of 900 amorphous glassy polymers. To develop a more general and implementable model for permeability prediction, we aim to build on the bases of Polymer Genome and develop a universal prediction model that covers a wide range of polymer classes.…”

Section: Introductionmentioning

confidence: 99%

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Polymer genome–based prediction of gas permeabilities in polymers

Zhu

Kim

Chandrasekarn

et al. 2020

Journal of Polymer Engineering

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Predicting gas permeabilities of polymers a priori is a long-standing challenge within the membrane research community that has important applications for membrane process design and ultimately widespread adoption of membrane technology. From early attempts based on free volume and cohesive energy to more recent group contribution methods, the ability to predict membrane permeability has improved in terms of accuracy. However, these models usually stay “within the paper”, i.e. limited model details are provided to the wider community such that adoption of these predictive platforms is limited. In this work, we combined an advanced polymer chemical structure fingerprinting method with a large experimental database of gas permeabilities to provide unprecedented prediction precision over a large range of polymer classes. No prior knowledge of the polymer is needed for the prediction other than the repeating unit chemical formula. In addition, we have incorporated this model into the existing Polymer Genome project to make it open to the membrane research community.

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Section: Model Performancementioning

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Polymer genome–based prediction of gas permeabilities in polymers

Zhu

Kim

Chandrasekarn

et al. 2020

Journal of Polymer Engineering

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“…Despite recent advances, measurements of silane permeability in membrane materials, in the presence of contaminants, have not been made with sufficient rigor to be used in membrane module design. Predictive methods to estimate permeability of gases in various polymer membrane materials is a promising complementary alternative but still depend on a database of experimental data [1,13]. Therefore, at the moment there is scarce information on the per-meability of silanes and other similar compounds of interest such as germanes.…”

Section: Introductionmentioning

confidence: 99%

Analysis of gas membrane ultra-high purification of small quantities of mono-isotopic silane

Almeida

Hart

2017

Journal of Membrane Science

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A small quantity of high-value, crude, mono-isotopic silane is a prospective gas for a small-scale, highrecovery, ultra-high membrane purification process. This is an unusual application of gas membrane separation for which we provide a comprehensive analysis of a simple purification model. The goal is to develop direct analytic expressions for estimating the feasibility and efficiency of the method, and guide process design; this is only possible for binary mixtures of silane in the dilute limit which is a somewhat realistic case. In addition, analytic solutions are invaluable to verify numerical solutions obtained from computeraided methods. Hence, here we provide new analytic solutions for the purification loops proposed. Among the common impurities in crude silane, methane poses a special membrane separation challenge since it is chemically similar to silane. Other potential problematic compounds are: ethylene, diborane and ethane (in this order). Nevertheless, we demonstrate, theoretically, that a carefully designed membrane system may be able to purify mono-isotopic, crude silane to electronics-grade level in a reasonable amount of time and expenses. We advocate a combination of membrane materials that preferentially reject heavy impurities based on mobility selectivity, and light impurities based on solubility selectivity. We provide estimates for the purification of significant contaminants of interest. In this study, we suggest cellulose acetate and polydimethylsiloxane as examples of membrane materials on the basis of limited permeability data found in the open literature. We provide estimates on the membrane area needed and priming volume of the cell enclosure for fabrication purposes when using the suggested membrane materials. These estimates are largely theoretical in view of the absence of reliable experimental data for the permeability of silane. Last but not least, future extension of this work to the non-dilute limit may apply to the recovery of silane from rejected streams of natural silicon semiconductor processes.

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“…The permeability coefficient can be represented as

P = D \cdot S,

where S is the solubility coefficient that determines the driving force of the process and D is the diffusion coefficient or kinetic component of P . It is well known that all three parameters ( P , D , and S ) depend on the chemical structure of a polymer; however, search for the reliable and accurate relationship between chemical structure and transport and sorption parameters of polymers remains a permanent concern of membrane researchers working with material design, that is, looking for and/or creating membrane materials with improved properties.…”

Section: Introductionmentioning

confidence: 99%

“…In the empirical group contribution methods, a statistical weight is assigned to every possible subgraph of a molecular graph, and the value of the index for a molecule is calculated as the weighted sum of numbers of occurrences of these subgraphs in the molecule. The group contribution method applied to repeat units of macromolecules of amorphous polymers (see Fig.…”

Section: Introductionmentioning

confidence: 99%

A novel model to predict infinite dilution solubility coefficients in glassy polymers

Goubko

Miloserdov

Yampolskii

et al. 2016

J Polym Sci B Polym Phys

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Infinite dilution gas solubility coefficients in glassy polymers of diverse chemical structure are predicted on the basis of a simple computational model of short polymer chain conformations. In contrast to existing models that describe the infinite dilution solubility coefficient S of various gases in certain polymers or S for the particular gas in different polymers, our approach allows to deal with the broad variety of gases and glassy polymers of different structure. With the van der Waals volume, accessible surface area, and some derivative geometrical descriptors being the predicting variables, the multivariate linear regression on the testing set gives correlation 0.89 with the logarithm of the solubility coefficient for the considered classes of relatively low‐permeable polymers (the mean relative error of solubility coefficient S prediction is 68%). Regression accuracy can be improved up to correlation 0.95 and the mean relative error 39% when a separate regression is constructed for each penetrant gas. Implications are discussed to the analysis of solubility selectivity. © 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2017, 55, 228–244

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A novel method for predictions of the gas permeation parameters of polymers on the basis of their chemical structure

Cited by 34 publications

References 46 publications

Polymer genome–based prediction of gas permeabilities in polymers

Polymer genome–based prediction of gas permeabilities in polymers

Analysis of gas membrane ultra-high purification of small quantities of mono-isotopic silane

A novel model to predict infinite dilution solubility coefficients in glassy polymers

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