  This work demonstrates how first-principles thermodynamic research within a
Bayesian framework can quantify and propagate uncertainties to downstream
thermodynamic calculations. To address the issue of Bayesian prior selection,
knowledge of zero Kelvin ground states in the material system of interest is
incorporated into the prior. The effectiveness of this framework is shown by
creating a phase diagram for the FCC Zirconium Nitride system, including
confidence intervals on phase boundary regions of interest.
