Quantifying uncertainty in DFT energy corrections

Density functional theory (DFT) is routinely used to estimate enthalpies of formation, phase stability, and other energy-derived properties. The accuracy of these estimates can be improved by using experimental thermodynamic data to develop energy corrections that remove some of the systematic error in DFT-computed properties. In this work, we demonstrate a method to quantify uncertainty in these energy correction values which captures uncertainty propagated from the underlying experimental data as well as sensitivity to the selection of fit parameters. We then incorporate this method into a new DFT energy correction scheme comprising a mixture of oxidation-state and composition-dependent corrections and show that many chemical systems contain unstable polymorphs that may actually be predicted stable when uncertainty is taken into account.