REGULARITIES OF MUTUAL SOLUBILITY OF MOLTEN SALT-LIQUID METAL SYSTEMS
熔盐—液体金属相互溶解度的规律性

Atomic parameter-artificial neural network method has been applied to study the regularities of the mutual solubility, the consolute temperatures, and the composition of monotectic points of molten salt-liquid metal systems. It has been found that larger melt's is correspond to lower mutual solubility. Trained artifical neural can be used to predict the consolute tempertures and the composition of monotectic points of molten salt-liquid metal systems. The error of the results of computerized prediction is rather small.