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AUTOMATION
To the 100-th anniversary of Academician Viktor V. Kafarov
ArticleName Obtaining method and computer optimization of ceramomatrix nanocomposites on the basis of carbon nanotubes
DOI 10.17580/tsm.2015.04.11
ArticleAuthor Koltsova E. M., Fedosova N. A., Diev A. N., Dudarov S. P.
ArticleAuthorData

D. Mendeleev University of Chemical Technology of Russia, Moscow, Russia:

E. M. Koltsova, Head of a Chair of Information Computer Technologies, e-mail: kolts@muctr.ru
N. A. Fedosova, Leading Programmer
A. N. Diev, Candidate for a Master's Degree
S. P. Dudarov, Dean

Abstract

This article considers the obtaining of composite, using carbon nanotubes as reinforcing element for corundum matrix. There was investigated the ultrasound impact on aqueous solutions of carbon nanotubes (solutions of ethanol, PVA, 2-propanol, and DMF). It is shown that PVA solution is more suitable for the compact samples' pressing, rather than DMF solution. Carbon nanotubes, obtained from methane-hydrogen gas mixture, made possible the obtaining of ceramic samples with uniform morphology, small grain size (3–5 mm), uniform distribution of carbon nanotubes on crystalfacets and both zero open and closed porosity. The flexural strength of the samples is about 400 MPa. A neural network approach was used to develop a mathematical model, which can be used to predict the nanocomposite properties. Creation of perception complex required the choice of six input parameters (amount of carbon nanotubes, maximum heating power, heating time, total time of intermediate holdings, number of intermediate holdings, interval of temperature increase) and five output characteristics (water absorption, linear shrinkage, open porosity, density, flexural strength). Target characteristic modeling is flexural strength value. On the basis of mathematical modeling results, there was made a definition that nanocomposite with carbon nanotubes' content from 3 to 5% (vol.) has optimum properties.
Researches were carried oud with the financial support of Russian Scientific Fund within the scientific project 14-19-00522.

keywords Composite material, carbon nanotubes, neuronetwork modeling, receiving nanocomposite
References

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