| Abstract Scope |
We discuss examples of uncertainty quantification of phase equilibrium in multi-component metals and ceramics. Thermodynamic data is generated via experiments and computer simulations that operate at various length and time scales, such as density functional theory, ab-initio molecular dynamics, phase field, finite elements, and calculations of phase diagrams (CALPHAD). The experimental and computational information is analyzed using machine learning coupled with Bayesian inference, resulting in optimal thermodynamic models with confidence intervals. The presentation includes a discussion of the unifying role of thermodynamics at the intersection of material, planetary and geological sciences. |