Electronic Structure Effect on Model Cluster for L1_2 Structure of Al_3Ti Intermetallic Compound with an Addition of Alloying Elements Fe, Ni and Cu

By use of self-consistent field Xα scattered-wave (SCF-Xα-SW) method, the electronic structure was calculated for four models of Ti4Al14X (X=Al, Fe, Ni and Cu) clusters. The Ti4Al14X cluster was developed based on L12 Al3Ti-base intermetallic compound. The results are presented using the density of states (DOS) and one-electron properties, such as relative binding tendency between the atom and the model cluster, and hybrid bonding tendency between the alloying element and the host atoms. By comparing the four models of Ti4Al14X cluster, the effect of the Fe, Ni or Cu atom on the physical properties of Al3Ti-based L12 intermetallic compounds is analyzed. The results indicate that the addition of the Fe, Ni or Cu atom intensifies the relative binding tendency between Ti atom and Ti4Al14X cluster. It was found that the Fermi level (EF) lies in a maximum in the DOS for Ti4Al14Al cluster; on the contrary, the EF comes near a minimum tn the DOS for Ti4Al14X (X=Fe, Ni and Cu) cluster. Thus the L12 crystal structure for binary Al3Ti alloy is unstable, and the addition of the Fe, Ni or Cu atom to Al3Ti is benefical to stabilize L12 crystal structure. The calculation also shows that the Fe, Ni or Cu atom strengthens the hybrid bonding tendency between the central atom and the host atoms for Ti4Al14X cluster and thereby may lead to the constriction of the lattice of Al3Ti-base intermetallic compounds.

Hydraulic metal structure health diagnosis based on data mining technology

In conjunction with association rules for data mining, the connections between testing indices and strong and weak association rules were determined, and new derivative rules were obtained by further reasoning. Association rules were used to analyze correlation and check consistency between indices. This study shows that the judgment obtained by weak association rules or non-association rules is more accurate and more credible than that obtained by strong association rules. When the testing grades of two indices in the weak association rules are inconsistent, the testing grades of indices are more likely to be erroneous, and the mistakes are often caused by human factors. Clustering data mining technology was used to analyze the reliability of a diagnosis, or to perform health diagnosis directly. Analysis showed that the clustering results are related to the indices selected, and that if the indices selected are more significant, the characteristics of clustering results are also more significant, and the analysis or diagnosis is more credible. The indices and diagnosis analysis function produced by this study provide a necessary theoretical foundation and new ideas for the development of hydraulic metal structure health diagnosis technology.