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铁道科学与工程学报

JOURNAL OF RAILWAY SCIENCE AND ENGINEERING

Vol. 8    No. 1    March 1998

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MOLTEN SALT PHASE DIAGRAMS CALCULATION USING ARTIFICIAL NEURAL NETWORK OR PATTERN RECOGNITION-BOND PARAMETERS
Part1. The prediction of the phase diagrams of binary molten salt systems
Wang Xueye1 Qiu Guanzhou1 and Wang Dianzuo1 Chen Nianyi2

1.Department of Mineral Engineering, Central South University of Technology, Changsha 410083, P. R. China;
2.Shanghai Institute of Metallurgy, Chinese Academy of Sciences, Shanghai200050, P. R. China

Abstract:Artificial neural network or pattern recognition together with chemical bond parameters method has been used to classify and predict the characteristics of the phase diagrams of binary molten salt systems. These characteristics are the formability, the chemical stoichiometry, the melting type and the melting point or decomposition temperature of intermediate compound and the formability of solid solution or eutectic mixture. The molten salt systems studied are some halide compounds such as MeX-Me’X, MeX-REX3 and MeX-Me’X4(Me, Me’denote metallic elements, RE rare earth, X halogen) systems. The mathematical models obtained from the experimental data of the known phase diagrams were used to predict the properties of the unknown phase diagrams.

 

Key words: phase diagram calculation artificial neural network pattern recognition bond parameter  binary molten salt system

ISSN 1672-7029
CN 43-1423/U

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