Combinatorial computational chemistry approach to the design of metal oxide electronics materials

Combinatorial chemistry has been developed as an experimental method where it is possible to synthesize hundreds of samples all at once and examine their properties. Recently, we introduced the concept of combinatorial approach to computational chemistry for material design and proposed a new method called 'a combinatorial computational chemistry'. In this approach, the effects of large number of dopants, substrates, and buffer layers on the structures, electronic states, and properties of metal oxide electronics materials is estimated systematically using computer simulations techniques, in order to predict the best dopant, substrate, and buffer layer for each metal oxide electronics materials. Recently, Kawasaki et al. constructed ZnO quantum dots on sapphire (0001) surface and observed an ultraviolet laser emission of the above materials. Although the band modulation techniques are essential to fabricate the electronics devices based on ZnO, experimentally it takes long time to optimize the best dopant for ZnO. Hence we applied the combinatorial computational chemistry technique to elucidate the effect of dopants on the structures, band, and optical properties of ZnO. Here, we employed a large number of dopants such as Mg, V, Cr, Mn, Fe Co, Cd, Pd, Pt, etc. and Mg was suggested as a best dopant for the wide band gap modulation. We also investigated the effects of large number of dopants in TiO₂ on its structure, band gap and photocatalytic activities. It is also confirmed that the periodic density functional theory combined the plane-wave basis and pseudopotential method is useful tools to explain the available experimental data and to design new functional materials based on metal oxides.