Integrating fundamental data with computational tools to predict materials properties is essential to improve materials design methods. This research will focus on the development and integration of first principle calculations; atomistic simulations; and/or thermodynamic, diffusion mobility, and molar volume CALPHAD-based databases with various computational tools to predict desired material properties (e.g., strength, fatigue) in structural materials. Essential to this process is the understanding of phase relations, phase transitions, processing-structure, and structure-property relationships. Equally important to the modeling efforts are the experimental characterizations of the process-structure and structure-property relations, and the development of database content. The developed models, knowledge, data, and software will be used to further the NIST effort to develop the materials innovation infrastructure central to the Materials Genome Initiative.

 

key words

Materials design; First principles; Atomistics; CALPHAD; Thermodynamics; Diffusion; Phase transitions; Materials Genome Initiative; Molecular dynamics;

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral applicants