Statistical-Thermodynamic Modeling of Key Materials

A statistical-thermodynamic modeling and prediction of the behavior of intermetallic compounds and thin film materials produced on their base under various technological states is of paramount importance, since these compounds are a fascinating group of materials, from the point of view of their fundamental properties and their technological application. Therefore, a generalized, quantitative and predictive statistical-thermodynamic modeling based on an Ising approach, the Bragg-Williams random-mixing approximations and the Bethe-Guggenheim quasi-chemical approximation is proposed for description of thermodynamic behavior and ordering phenomena in bulk and nano-crystalline ordered intermetallic materials. The new modeling approach takes into account the presence of all possible defects in the structure, both vacancies and anti-structure atoms and includes a description of Long-Range Ordering and Short-Range Ordering in the crystal lattice, i.e. the possible correlation of nearest neighbor point defect combinations.
The proposed new modeling approach and developed models will encompass a predictive ability and a general application to understanding of ordering processes in the structure and to improvement of the mechanical and thermodynamical properties of existing intermetallic bulk and nano-crystalline commercial materials, and also in new advanced materials discovery and development. In addition, it provides strategies for refinement of scientific concepts and carrying out the research in a productive manner, avoiding expensive or even dangerous experiments in the laboratory.