1. Polymer genome–based prediction of gas permeabilities in polymers
- Author
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Anand Chandrasekarn, Joshua D. Everett, Rampi Ramprasad, Guanghui Zhu, Chiho Kim, and Ryan P. Lively
- Subjects
chemistry.chemical_classification ,Materials science ,Polymers and Plastics ,Polymer science ,General Chemical Engineering ,Industrial chemistry ,02 engineering and technology ,Polymer ,010402 general chemistry ,021001 nanoscience & nanotechnology ,01 natural sciences ,Genome ,0104 chemical sciences ,Membrane ,chemistry ,Materials Chemistry ,Gas separation ,0210 nano-technology - Abstract
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.
- Published
- 2020
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