金属离子-DCyTA配合物稳定性的函数连接型网络研究

Study on the Stabilities of DCyTA Complex of Metal Ions by using Artificial Neural Network

采用函数连接型神经网络的方法 ,以金属离子的电荷、离子半径、价电子结构、电负性及适配价轨道数因子为参数 ,成功地关联了4 6种已知的金属 DCyTA配合物稳定常数logK值 ,并在此基础上 ,预报了包括所有锕系元素在内的 2 2种金属 DCyTA配合物的logK值。

A functional-link net(FLN) was applied to study the relationships between the structural parameters of metal ions and their stability constants of EDTA complexes. Some of the absent stability constants of DCyTA complexes of metal ions were predicted with the method. The results are satisfactory and the prediced values are referable.