Designing of Flux Composition in Copper Alloy Melting Process to Achieve Good Balance between Suppression of Refractory Corrosion and Acceleration of MnO Dissolution into Flux Using Neural Network and Thermodynamic Computation

A new method of designing a flux for the copper alloy melting process that can achieve a good balance between the suppression of refractory corrosion by the flux and the acceleration of MnO dissolution into the flux was proposed. In this study, NN (neural network) computation was used to evaluate the refractory corrosion by the flux, and the predicted amounts of corrosion of refractories were in good agreement with experimental data. For the evaluation of the properties related to the MnO dissolution into the flux, both the viscosity of fluxes and the activity of MnO in fluxes were examined using thermodynamic analysis. By integrating the results of the above evaluations, an efficient method of designing the flux composition was devised. As an example of the application for this method, SiO2-55 mass％ Na2O flux was found to be the optimal flux when Al2O3 refractory was employed.