摘要
用化学结构参数- 模式识别人工神经网络方法对非晶态合金系的磁性、超导电性和力学性能( 包括饱和磁致伸缩系数、饱和磁感应强度、矫顽力、超导转变温度、硬度和抗拉强度) 与组成结构之间的关系进行了定性分析和定量计算,采用的化学结构参数为平均价电子数、混合熵、原子半径比、电负性差、功函数差和电子密度差等.结果表明,定性分析结果与实验结论一致,定量计算结果与实验测定值符合较好.
Computer aided material design is a growing branch of science, and is unquestionably of great importance in modern chemistry, biochemistry and material science. First, the mechanical properties including hardness and tensile strength for amorphous alloys had been analyzed and calculated, by the PLS and ANN method with the average valence-electron number, mixed entropy, ratio of metallic radii and electronegativity difference as features or inputs. The results indicate that the hardness and tensile strength increase with the increase of four parameters, and the calculated values are in agreement with the experimental ones basically. Second, the magnetic properties of thirty amorphous alloys had been discussed of PLS method with electron concentration, ratio of radii, difference of electron density, difference of work function and mixed entropy as features. In addition, the calculated results of ANN method for magnetic properties are inspiring as compared with experimental values. Finally, the superconductivity for thirty-nine amorphous alloys hand been investigated, by PLS and ANN method with the same structural chemical parameters.
出处
《湘潭大学自然科学学报》
CAS
CSCD
1999年第4期68-73,共6页
Natural Science Journal of Xiangtan University
关键词
非晶态合金
结构-性能关系
磁性
力学性能
amorphous alloys, structure-property relationship, structural parameter