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

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Abstract

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
Volume1994
Issue number86
DOIs
Publication statusPublished - 1994

Keywords

  • METIS-106906
  • IR-12725

Cite this

Wessling, M., Mulder, M. H. V., Bos, A., Bos, A., van der Linden, M. K. T., Bos, M., & van der Linden, W. E. (1994). Modelling the permeability of polymers: a neural network approach. Journal of membrane science, 1994(86), 193-198. https://doi.org/10.1016/0376-7388(93)E0168-J