Modelling the permeability of polymers: a neural network approach

Matthias Wessling, M.H.V. Mulder, A. Bos, A. Bos, M.K.T. van der Linden, M. Bos, W.E. van der Linden

Research output: Contribution to journalArticleAcademicpeer-review

13 Citations (Scopus)
84 Downloads (Pure)


In this short communication, the prediction of the permeability of carbon dioxide through different polymers using a neural network is studied. A neural network is a numeric-mathematical construction that can model complex non-linear relationships. Here it is used to correlate the IR spectrum of a polymer to its permeability. The underlying assumption is that the chemical information hidden in the IR spectrum is sufficient for the prediction. The best neural network investigated so far does indeed show predictive capabilities.
Original languageUndefined
Pages (from-to)193-198
Number of pages6
JournalJournal of membrane science
Issue number86
Publication statusPublished - 1994


  • METIS-106906
  • IR-12725

Cite this