Elucidating the Thermodynamic and Kinetic Properties of High Temperature Materials with First-Principles Statistical Mechanics

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NON-TECHNICAL SUMMARY Remarkable levels of sophistication have been reached in linking properties of a given material to its microstructure, crystal structure and electronic structure. A substantially bigger challenge, though, is predicting the dynamic evolution of a material taken out of equilibrium and determining what external stimuli must be imposed to shepherd the material into a desired end state. The desirable properties from a particular chemistry are usually manifested in metastable crystal structures and microstructures rather than in the true equilibrium state of that chemistry. In many applications it is necessary to know how a material in a particular state will evolve over time either because it is metastable or unstable, such as in high temperature applications, or due to changing boundary conditions, as in electrochemical energy storage applications.This award supports computational research and education to develop highly automated statistical mechanical software tools that will be used to predict materials properties and greatly enhance the ability to design materials for high temperature and non-equilibrium applications from first principles. Areas where such tools will prove invaluable include the design of new (i) structural materials for aerospace applications and large-scale power generation plants, (ii) electrode and electrolyte materials for electrochemical energy storage, (iii) materials for thermoelectric applications and (iv) materials for shape memory applications. The project will also involve the education and training of graduate students in computational materials science, a field that is increasingly recognized as invaluable in the design and rapid implementation of new materials.TECHNICAL SUMMARY This award supports research and educational activities aimed at extending the existing thermodynamic and kinetic foundations that underpin phenomenological descriptions of non-equilibrium processes in the solid state. This will be realized by two activities: (i) the development of statistical mechanical computational tools to automate the calculation of a wide variety of thermodynamic and kinetic properties that are essential in the description of materials evolving out of equilibrium and (ii) the development and application of new statistical mechanical theoretical methods to enable the prediction of high temperature properties of multi-component crystalline solids. A deep understanding of many high temperature materials and non-equilibrium processes is hampered by a lack of not only quantitative thermodynamic, kinetic and mechanical data, but also a lack of knowledge about qualitative trends in this data. Furthermore, a large class of technologically important high temperature materials cannot be adequately described and understood with current statistical mechanical methods. This research activity will result in highly automated computational statistical mechanical tools to predict free energies and transport coefficients as a function of concentration. Such tools will provide new knowledge about the dependence of a wide variety of materials properties on chemistry and crystal structure. The theoretical focus on high temperature phases will generate fundamental new insights about the vibrational stabilization mechanisms, atomic hop mechanisms and mechanical properties of a large and important class of poorly understood materials used in high temperature applications. The project will also involve the education and training of graduate students in computational materials science, a field that is increasingly recognized as invaluable in the design and rapid implementation of new materials.