【摘要】 利用动态聚类分析、最小生成树、主成分分析等模式识别方法 ,对含ZnO半导体材料的样本集中各样本之间在 30 0K时的晶格匹配与热匹配程度进行了分析。结果表明 :在 30 0K时 ,三种Ⅲ -Ⅴ族氮化物AlN、GaN、InN与ZnO材料之间的晶格匹配和热匹配程度最好。由最小生成树以及主成分二维映射结果可知两类样本分区明显 ,分类效果良好 ,表明利用模式识别方法可对含ZnO样本集中各样本之间的晶格匹配和热匹配程度进行识别更多还原

【Abstract】 Some pattern recognition methods including dynamic clustering analysis, minimal spanning tree and principal component analysis have been used to recognize the extents of both lattice-match and thermo-match at 300K for the samples containing ZnO semiconductor material. From the pattern recognition analysis, it is concluded that there exists a lower lattice and thermal misfits between ZnO and three Ⅲ-Ⅴgroup nitrides. The results also show that pattern recognition analysis seems to be a suitable tool to select substrate or buffer layer for epitaxy growth, as well as to design optoelectronic devices of blue and violet light semiconductor materials, such as ZnO and GaN.更多还原