Multiscale computational materials science has reached a stage where many complicated phenomena or properties that are of great importance to manufacturing can be predicted or explained. The word “ab initio study” becomes commonplace as the development of density functional theory has enabled the predictions to be independent of experimental data or empirical parameters. For some crucial phenomena, e.g., precipitation processes in multicomponent alloys, however, challenges exist due to the requirement of an accurate and efficient description of both energetics and kinetics of a complex system. In the present thesis, a systematic methodology has been established for predicting the morphology and realistic formation kinetics of precipitates in multicomponent alloys. Aluminum alloys are chosen as prototype applications of the present methodology, because of the well-known strengthening mechanism—age or precipitation hardening which is a typical and important precipitation process utilized in industrial materials. As one of the main computational approaches, cluster expansion technique is applied to study vacancy properties in concentrated Cu-Ni alloys. Diffusion kinetics in dilute Al-Cu alloys including the role of multiple diffusion barriers has been investigated by kinetic Monte Carlo simulations. At finite temperature, electronic entropy contribution to the free energies of the transition metals is also discussed.@en

It is shown that in substitutional alloys, peculiar ordered patterns can result from neighborhood-dependent diffusion activation barriers even when there are no metastable ordered phases. Lattice gases with pure phase separation character are shown to exhibit transient ordered structures that can be retained almost indefinitely, although these structures are not at thermodynamic equilibrium. It is shown that such structures can come about relatively easily by quenching from the high-temperature configurationally random solid solution.@en

The temperature-dependent intrinsic stacking fault Gibbs energy is computed based on highly converged density-functional-theory (DFT) calculations for the three prototype face-centered cubic metals Al, Cu, and Ni. All relevant temperature-dependent contributions are considered including electronic, vibrational, magnetic, and explicit anharmonic Gibbs energy contributions as well as coupling terms employing state-of-the-art statistical sampling techniques. Particular emphasis is put on a careful comparison of different theoretical concepts to derive the stacking fault energy such as the axial-next-nearest-neighbor-Ising (ANNNI) model or the vacuum-slab approach. Our theoretical results are compared with an extensive set of previous theoretical and experimental data. Large uncertainties in the experimental data highlight the necessity of complementary parameter-free calculations. Specifically, the temperature dependence is experimentally unknown and poorly described by thermodynamic databases. Whereas calphad derived data shows an increase of the stacking fault energy with temperature for two of the systems (Cu and Ni), our results predict a decrease for all studied systems. For Ni, the temperature induced change is in fact so strong that in the temperature interval relevant for super-alloy applications the stacking fault energy falls below one third of the low temperature value. Such large changes clearly call for a revision of the stacking fault energy when modeling or designing alloys based on such elements.@en