Modelling the permeability of polymers: a neural network approach

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.