Abstract: The resistance of a TiO2 anatase (001) surface to coke formation was studied in the context of dry reforming of methane using density functional theory (DFT) calculations. As carbon atoms act as precursors for coke formation, the resistance to coke formation can be measured by the carbon coverage of the surface. This is related to the stability of different CHx (x = 0−3) species and their rate of hydrogenation and dehydrogenation on the TiO2 surface. Therefore, we studied the reaction mechanisms and their corresponding rates as a function of the temperature for the dehydrogenation of the species on the surface. We found that the stabilities of C and CH are significantly lower than those of CH3 and CH2. The hydrogenation rates of the different species are significantly higher than the dehydrogenation rates in a temperature range of 300−1000 K. Furthermore, we found that dehydrogenation of CH3, CH2, and CH will only occur at appreciable rates starting from 600, 900, and 900 K, respectively. On the basis of these results, it is clear that the anatase (001) surface has a high coke resistance, and it is thus not likely that the surface will become poisoned by coke during dry reforming of methane. As the rate limiting step in dry reforming is the dissociative adsorption of CH4, we studied an alternative approach to thermal catalysis. We found that the temperature threshold for dry reforming is at least 700 K. This threshold temperature may be lowered by the use of plasma-catalysis, where the appreciable rates of adsorption of plasma-generated CHx radicals result in bypassing the rate limiting step of the reaction.

Abstract: Density functional theory is widely used to gain insights into molecule−metal surface reaction networks, which is important for a better understanding of catalysis. However, it is well-known that generalized gradient approximation (GGA)
density functionals (DFs), most often used for the study of reaction networks, struggle to correctly describe both gas-phase molecules and metal surfaces. Also, GGA DFs typically underestimate reaction barriers due to an underestimation of the selfinteraction energy. Screened hybrid GGA DFs have been shown to reduce this problem but are currently intractable for wide usage. In this work, we use a more affordable meta-GGA (mGGA) DF in combination with a nonlocal correlation DF for the first time to study and gain new insights into a catalytically important surface
reaction network, namely, CO2 hydrogenation on Cu. We show that the mGGA DF used, namely, rMS-RPBEl-rVV10, outperforms typical GGA DFs by providing similar or better predictions for metals and molecules, as well as molecule−metal surface adsorption
and activation energies. Hence, it is a better choice for constructing molecule−metal surface reaction networks.