The least-squares anchor set is particularly advantageous for comparing energies from different sources or approximations. When using specific molecular species as anchors A, any error associated with the species will propagate through ∆ A H of the entire dataset. To illustrate this, Fig. compares the relative enthalpies of species in the oxidative dehydrogenation of ethane for two different xc functionals, RPBE and BEEF-vdW. Relative enthalpies are computed using the elemental chemical potential approach with two different reference anchor sets and the least-squares anchor. Using the molecular anchors, the deviation between the two functionals varies widely depending on the choice of anchor species. Naive comparisons could lead to very different conclusions about the relative performance of these two xc functionals. On the other hand, using the entire reaction mechanism to determine the anchor chemical potentials by minimizing the sum of squared errors removes the arbitrary dependence on the choice of anchor species. When using these fitted chemical potentials, the scatter and, accordingly, the deviation between the xc functionals are significantly smaller. This behavior is also displayed in Fig. , where ∆ LS H derived from the RPBE and BEEF-vdW functional give similar results with only small deviations. Determining the chemical potentials via linear regression does not make the DFT energetics more accurate; all reaction energies will be unaffected, as shown in Eq. ( ). However, it makes the energetic data from different xc functionals more comparable, as seen in Fig. .