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Composite materials have changed the way of
using polymers, as the strength was favored by the incorporation
of fibers and particles. This new class of materials allowed
a larger number of applications. The insertion of nanometric
sized particles has enhanced the variation of properties with
a smaller load of fillers. In this paper, we attempt to a
better understanding of nanocomposites by using an artificial
intelligence’s technique, known as artificial neural networks.
This technique allowed the modeling of Young’s modulus of
nanocomposites. A good approximation was obtained, as the
correlation between the data and the response of the network
was high, and the error percentage was low.
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