(中国科学院上海冶金研究所， 上海 200050;
*北京师范大学， 北京 100081)
摘 要: 用rMe, rMe', rX, xMe和xMe'等原子参数作为人工神经网络的输入， 203个可信的Me-Me'-X体系的三元化合物的形成情况作为输出，研究了Me-Me'-X系三元化合物的形成规律，这里r是离子半径，x是电负性， Me代表一价金属， Me'代表二价金属，X代表卤族元素。利用所得规律预报了M-Eu-I（M=Li，Na， K， Rb和Cs）系三元碘化物的形成情况， 应用差热分析和粉末X射线法测定了它们的相图，预报结果和实验测定结果的对比是令人满意的。
关键字: 三元化合物 相图 计算机预报 人工神经网络
（Shanghai Institute of Metallurgy, Chinese Academy of Sciences, Shanghai 200050, P. R. China;
* Beijing Normal University, Beijing 100081, P. R. China）
Abstract:Using the atomic parameters of rMe, rMe', rX, xMe and xMe as the inputs, the regularity of formation of ternary complex halides of MeMe'-X halides systems has been investigated by artificial neural networks（ANNs）. Where, r is the radius of the ion, x is the electronegativity of element, Me is the mono-valent metal, Me' is di-valent metal, X represents the F, Cl, Br or I. The regularity was found by training the ANNs with 203 known samples (such as Ag-Ca-Cl system and K-Mg-Cl system etc.). The formation of ternary complex iodides in M-Eu-I systems (where M represents Li, Na, K, Rb or Cs) was predicted by this trained ANNs. The predicted results are completely in agreement with the experimental facts.
Key words: ternary compound phase diagram computer prediction artificial neural network
