Enhanced works of separation for (0001) ZnO vertical bar(111) ZrO2 interfaces via ion-doping in ZnO: Data-mining and density function theory study

The enhanced works of separation for the low adhesive (0001) ZnO vertical bar(111) ZrO2 interfacess via Y-doping in ZnO slab were systematically studied using data-mining technique and density functional theory (DFT) study. The lattice constants in 31 types of doped wurtzite Zn0.9375X0.0625O were evaluated from DFT calculations. No linear correlation is found between the lattice constants and atomic radii. A support vector regression (SVR) for the lattice constants of 32 Zn0.9375X0.0625O has been performed. SVR method with leave-one-out cross-validation is used for evaluating the regression models. The correlation coefficient obtained by the models was 0.905. The accuracy of SVR model was higher than those of artificial neural network (ANN) and partial least square (PLS) methods. Zn0.9375Y0.0625O has the largest lattice constants among the investigated systems. In Y-ZnO(0001) surface, a significant segregation phenomena occurs. Hence, dopant Y expands the lateral lattice and leaves the Zn-terminal surface intact. For coherent (0001) Y-ZnO vertical bar(111) ZrO2 interfaces, Y-doping can enhance the work of separation significantly (similar to 82%) compared with the undoped (0001) ZnO vertical bar(111) ZrO2 interfaces. (C) 2017 Elsevier B.V. All rights reserved.