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https://doi.org/10.37358/Rev.Chim.1949

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Revista de Chimie (Rev. Chim.), Year 2011, Volume 62, Issue 10,





Constantin Luca, Ana-Maria Grigoriu, Rodica Mariana Diaconescu, Marius Secula
Modeling and Simulation of Monochlorotriazinyl-b-cyclodextrin
Paper Grafting by Artificial Neural Network

Abstract:

This study presents the neural network modeling of monochlorotriazinyl-b-cyclodextrin (MCT-b-CD) grafting on paper supports. Neural networks are very efficient in predicting the evolution of a process, providing a good approximation of the studied grafting process, further used for the interpolation and extrapolation of the results beyond the experimental range. The grafting was realized by a pad-dry-cure treatment and the mathematical model has quantified the influence of the real independent variables (i.e concentrations of MCT-b-CD and of the catalyst temperature) on the grafting degree as goal function. The treated paper samples were analyzed by FT-IR-ATR spectroscopy and SEM, in order to prove the grafting of the cellulosic support. Keywords: artificial neural network, modeling and simulation, grafting, nanocoated paper


Issue: 2011, Volume 62, Issue 10
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