Cai Yuxiang, Michiels Roel, De Luca Federica, Neyts Erik, Tu Xin, Bogaerts Annemie, Gerrits Nick
Research Group PLASMANT, Department of Chemistry, University of Antwerp, Universiteitsplein 1, Antwerp, Wilrijk BE-2610, Belgium.
Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 3GJ, U.K.
J Phys Chem C Nanomater Interfaces. 2024 May 17;128(21):8611-8620. doi: 10.1021/acs.jpcc.4c01110. eCollection 2024 May 30.
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 self-interaction 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, CO 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.
密度泛函理论被广泛用于深入了解分子 - 金属表面反应网络，这对于更好地理解催化作用非常重要。然而，众所周知，最常用于研究反应网络的广义梯度近似（GGA）密度泛函（DFs）在正确描述气相分子和金属表面方面存在困难。此外，由于自相互作用能的低估，GGA DFs通常会低估反应势垒。筛选混合GGA DFs已被证明可以减少这个问题，但目前难以广泛使用。在这项工作中，我们首次使用一种更经济实惠的元GGA（mGGA）DF与非局部相关DF相结合，来研究一个具有催化重要性的表面反应网络，即铜上的CO加氢反应，并获得新的见解。我们表明，所使用的mGGA DF，即rMS - RPBE1 - rVV10，通过对金属和分子以及分子 - 金属表面吸附和活化能提供相似或更好的预测，优于典型的GGA DFs。因此，它是构建分子 - 金属表面反应网络的更好选择。
