物理化学学报 >> 1996, Vol. 12 >> Issue (09): 809-811.doi: 10.3866/PKU.WHXB19960907

研究论文 上一篇    下一篇

ANN原子参数法预报合金相晶型及晶格常数

姚树文,郭进,王学业,陈念贻   

  1. 中国科学院上海冶金研究所,上海 200050
  • 收稿日期:1996-03-25 修回日期:1996-05-27 发布日期:1996-09-15
  • 通讯作者: 陈念贻

ANN-Atomic Parameter Method Applied to Prediction of Crystal-type and Lattice Constants of Alloy Phases

Yao Shu-Wen,Guo Jin,Wang Xue-Ye,Chen Nian-Yi   

  1. Shanghai Institute of Metallurgy,Chinese Academy of Sciences,Shanghai 200050
  • Received:1996-03-25 Revised:1996-05-27 Published:1996-09-15
  • Contact: Chen Nian-Yi

摘要:

运用人工神经网络方法,以二元合金组成元素的电子结构为基本特征,对二元合金相晶型作了区分,进一步对其晶格常数作了预报,结果令人满意.

关键词: 人工神经网络, 原子结构, 晶型, 晶格常数

Abstract:

 Artificial neural network method has been applied to the computerized prediction of the crystal type and lattice constants of binary alloy phases by using atomic parameters of the constituent elements, the results obtained are satisfactory.

Key words: Artificial neural network, Atomic structure, Crystal type, Lattice constant