Using Artificial Neural Networks to Predict Physical Properties of Membrane Polymers
- University of Kansas, Lawrence, KS (United States); University of Kansas
- University of Kansas, Lawrence, KS (United States)
Membrane polymers are a promising technology for use in many challenging gas separation applications. Here, the techniques of computer-aided molecular design can be used to search through the massive molecular space of heteropolymers and develop a set of likely candidate repeat units matching specific physical property targets. However, reasonably accurate property prediction algorithms are needed, but these algorithms must be very fast in order to be combined with an optimization framework. Artificial neural networks (ANNs), a branch of machine learning, are applied in this work to predict the physical properties of polymers. All of the physical properties investigated were found to be predicted by ANNs with R2 scores exceeding 0.82.
- Research Organization:
- RAPID Manufacturing Institute, New York, NY (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- Grant/Contract Number:
- EE0007888
- OSTI ID:
- 2007302
- Journal Information:
- Chemie-Ingenieur-Technik, Journal Name: Chemie-Ingenieur-Technik Journal Issue: 3 Vol. 95; ISSN 0009-286X
- Publisher:
- WileyCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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