(514h) Unifying Thermochemistry Concepts in Computational Heterogeneous Catalysis

The most important quantity in microkinetic models is the Gibbs free energy of formation. It quantifies the stability of intermediates (gas-phase species or adsorbates), determines the catalyst morphology under reaction conditions, and defines the thermodynamic equilibrium. The Gibbs free energy of formation is calculated from the enthalpy of formation and entropy. Entropy is a species-specific property derived from the partition functions of the species. However, the enthalpy of formation is a species-interrelated quantity and only meaningful with a reference. The gas-phase community has established standards and frameworks to create global thermochemical networks with data from electronic structure theory and experiments that provide highly accurate enthalpies of formation. In the computational heterogeneous catalysis community, no standards currently exist to compute enthalpies of formation due to the large uncertainty of DFT (which is the only feasible level of theory), the absence of a clear hierarchy of methods, and limited experimental data. Thus, various methods are reported in the literature, where each group uses its definitions, conventions, and corrections. This myriad of approaches makes accessing, comparing, integrating, or analyzing data from different sources challenging.

In this work, we present all available methods to derive enthalpies of formation from DFT data using the oxidative dehydrogenation of C₂H₆ on Pt(111) as a case study. We show that these different concepts can be unified with a consistent notation using a set of linear algebra tools to compute the thermophysical properties for microkinetic models. The available methods can be grouped according to the construction of local and global thermochemical networks. Further, we highlight each method's assumptions, benefits, and drawbacks. Our goal with this study is to start a discussion with the community to establish new standards for computational catalysis that facilitate the re-use and sharing of data.