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EN
This study concerns the application of artificial neural networks in oxidation kinetic analysis of ceramic nanocomposites. The oxidation of the Ti-Si-C ceramic nanocomposite in dry air was studied. The size of the nanoparticles was determined by scanning electron microscopy (SEM). The gaseous oxidation products were analysed by mass spectroscopy (MS) while the solid oxidation products by X-ray diffraction (XRD). The kinetic analysis of the oxidation was based on the Coats-Redfern equation. The kinetic models were identified for the consecutive stages and then the A and E parameters of the Arrhenius equations were evaluated. Artificial neural networks were used at each step of the kinetic calculations.
EN
In this work, the results of investigations of manufacturing ceramic materials on the basis of Ti, B, C and N containing systems are presented. The nanocrystalline ceramics were synthesized using a non-hydrolytic sol-gel method. The process was carried out in two stages. In the first low-temperature stage the precursor was obtained. The synthesis of ceramic phases, however, was conducted in the second high-temperature stage, in an argon atmosphere. Depending on the initial composition of the mixtures, the temperature and the time, the following products were obtained: TiCx, TiCxN1−x, TiB2 and B4C. The course of the process was investigated by thermogravimetric and differential scanning calorimetry methods (TG-DSC) coupled with mass spectrometry (MS). The solid state products were identified with use of X-ray diffraction (XRD). The size of the crystallites was estimated by the Scherrer method. The structure and morphology images of nanocrystalline powders were obtained using scanning electron microscopy (SEM) and transmission electron microscopy (TEM).
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