Computational tools for the prediction of materials properties are essential for materials design methods. Equally important is the knowledge of the uncertainty associated with the results from these tools. A number of computational materials science tools are built on computational thermodynamics. The CALPHAD (CALculation of PHAse Diagrams) method is a proven, indispensable tool in this endeavor but lacks uncertainty quantification of the results. Development of a systematic approach for rigorous assessment of uncertainties in CALPHAD results is needed. This approach should use principles widely adopted in metrology and statistics, and are in harmony with NIST uncertainty guidance documents. The developed models, knowledge, data, and software will be used to further the NIST effort in development of uncertainty quantification tools within the framework of the Materials Genome Initiative.

 

Keywords:

Computational thermodynamics; CALPHAD; Materials Genome Initiative; Uncertainty quantification; Statistics; Numerical analysis;

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral applicants