In the present paper, all-electron full-potentialab initio simulation method with mixed-basis is introduced and several typical examples are indicated which successfully show the possibility of predicting properties of materials prior to actually carrying out the experiments. We have used theab initio calculation to extract energy parameters, and apply them to cluster variation and direct methods, which bridge the limited space ofab initio treatment to real complex materials. To overcome the limited computer power, we have also developed parallel processing codes and tested their efficiencies.

In this paper we have presented all-electron full-potentialab initio simulation method with introduction of mixed-basis, and have cited several typical examples which indicate that it is possible to predict properties of materials prior to experimental. Based on theab initio calculation of the total energy, cluster variation, and direct methods function, it is possible to bridge the limited scheme of theab initio treatment to real complex materials. Furthermore, to overcome the limited computer power, we have developed parallel processing codes and tested their efficiencies as well.

Ab initio treatment is becoming realistic to predict physical, chemical, and even mechanical properties of academically and industrially interesting materials. There is, however, some limitation in size and time of the system up to the order of several hundred atoms and ∼ 1 pico second, even if we use the fastest supercomputer efficiently. Therefore, it is very difficult to simulate realistic materials with grain boundaries and important reactions like diffusion in materials. To improve this situation, two ways have been invented. One way is to upgrade approximations to match the necessary levels according to inhomogeneous electron gas theory beyond the present day standard, i.e. local density approximation (LDA). The reason is simply that the system we are interested in is composed of many particles interacting with Coulomb forces governed by quantum mechanics. (Complete knowledge is available, and only what we should do is to make better approximations to explain the phenomena!). Another is to extract the necessary parameters from the ab initio calculations on systems with limited number of atoms, and apply these results into cluster variation, direct, or any other sophisticated methods based on classical concepts such as statistical mechanics.

In this paper, several typical examples recently worked out by our research group are introduced to indicate that these methodologies are actually possible to be successfully used to predict materials properties before experiments based on the present day state-of-art supercomputing systems. It includes scientific visualization of the results of ab initio molecular dynamics simulation on atom insertion process to C₆₀ and to carbon nanotube, tight-binding calculation of single electron conductance properties in nanotube to create nano-scale diode virtually by computer, which will be a base of future nanoscale electric device in nanometer size, Li + H reaction without Born–Oppenheimer approximation, structural phase transitions in perovskite materials under very high pressure in earth by direct method, and prediction of wavelength of emitted light from Na clusters with GW (G = Green function-vertex, W = screened Coulomb interaction) approximation.

The geometries of several Mn clusters in the size range Mn₁₃–Mn₂₃ are studied via the generalized gradient approximation to density functional theory. For the 13- and 19-atom clusters, the icosahedral structures are found to be most stable, while for the 15-atom cluster, the bcc structure is more favoured. The clusters show ferrimagnetic spin configurations.