S. K. Vildanov.
ABSTRACT
We obtained the ratio for calculating the viscosity of multicomponent oxide solution based on SiO2 depending on the ionic fractions of cations that make up the oxide solution. This allows us to predict the concentration change in viscosity and to calculate its value using data on the viscosity of liquid solutions of two-component systems SiO2–MexOy in the concentration range of silicon dioxide 65–75 weight % for fixed temperatures. The conclusion of the ratio is based on the idea of an oxide solution as a superposition of elementary structures of the arrangement of cations relative to each other. Moreover, cations of the same sort are located around the oxygen anion. The cationic sites are filled in such a way that four cations of the same sort are located around the oxygen anion. The accepted model assumes that all cations have the same dimensions and the same charge, but differ only in grade. The resulting calculation formula is a polynomial. To find unknown coefficients in the equation for viscosity as a function of composition, a probabilistic model is proposed that takes into account the order of extraction of cations from the cationic mixture under the assumption that the nature of the change in viscosity as a function of composition is similar to the probability of extracting a certain set of cations from a cationic mixture. For the activation viscosity model, regression relations are obtained for the dependence of the activation energy of the viscous flow and the preexponential factor on the ionic fraction of the second component of the SiO2–MexOy systems. Comparative calculations of viscosity values are carried out using the calculation formula with experimental data on the viscosity of multicomponent oxide silicate melts. The results of the comparative analysis showed a satisfactory agreement between the calculated viscosity values and experimental data.
KEYWORDS:
viscosity, oxide solution, oxide melt, cationic mixture, metal, heat-insulating slagforming mixture, experiment, probabilistic model, conditional probability, model oxide solution, energy, matrix
DOI: 10.31857/S0235010620040106