(392b) Mechanistic Insights into CO2 Hydrogenation on Transition Metal Surfaces: A DFT- Based Microkinetic Analysis

Avanesian, T. - Presenter, University of California, Riverside
Christopher, P. - Presenter, University of California, Riverside

Recent interest in selective CO2 hydrogenation to useful fuels and chemicals has motivated the development of new catalytic materials that exhibit high selectivity in desired transformations. However, many fundamental details of CO2 hydrogenation on transition metal surfaces are still missing.  Of particular interest is uncovering descriptors that can be related to previously observed dependence of metal composition to reaction selectivity.  Most notably, the trend between CO and CH4 selectivity in CO2 hydrogenation on transition metals has not yet been explained.

We utilize ab-initio density functional theory (DFT) computational methods to develop molecular level insights into the mechanisms that control the performance and selectivity of metal catalysts in CO2 hydrogenation. A thorough mechanistic study of CO2 hydrogenation on a model Ru(0001) catalyst surface was executed, to address fundamental mechanistic questions and existing debates in literature regarding the CO2 hydrogenation pathways. The complete energetic pathway of the reaction is mapped out using DFT calculated energetics of the reaction intermediates and activation barriers of the elementary steps. The possible reaction paths and probability of competing reactions such as reverse water gas shift reaction are investigated by comparison of the energetic levels of elementary steps. The calculated energetics and vibrational frequency analysis are used to perform a microkinetic modeling of the reaction, which identifies the most stable surface species, the performance limiting and selectivity controlling steps. The results of our analyses on Ru(0001) are extended through the use of the “degree of catalyst control” to explain experimentally observed trends in CO2 hydrogenation selectivity among transition metals and develop simple descriptors of selectivity.