Methane slip from natural gas engines poses a great challenge for the transition to natural gas as alternative transportation fuel. Platinum group metals (PGMs) are active for complete methane oxidation and their activity can be further improved when combined with spinel oxides (AB2O4), especially under dynamic lean/rich cycling conditions. The role of the spinel oxide is to directly oxidize methane at elevated temperature and serve as oxygen storage material for reactions on PGM sites. These functions are governed by two critical descriptors: the oxygen vacancy formation energy (Evac) and hydrogen binding energy (EH). As the spinel structure spans a vast composition space, it presents an ideal platform for property tuning. To this end, we have used density functional theory (DFT) calculations and machine learning to screen spinel structures based on Cr, Mn, Fe, Co, Ni, Cu, Zn, Li, Mg, and Sn to assess their phase stability and identify candidates with high intrinsic methane oxidation activity and dynamic oxygen storage capacity. For Fe3O4 we also investigated the effect of PGM promotion on CH4 conversion under dynamic conditions. The two critical descriptors of C-H activation on oxide catalysts (Evac, and EH) were found to be linearly dependent on each other (Fig. 1a). Through a machine learning approach, we could propose an empirical model that captures the reducibility features of 83 experimentally reported spinels. Some of the most promising spinels were synthesized with reduced precious metal loading and demonstrated the theoretically predicted improved low temperature methane oxidation activity (Fig. 1b). Methane activation below 350 °C on these low-cost PGM/spinel oxide-based catalysts is a promising step towards meeting the US-EPA targets for tailpipe methane emissions from natural-gas vehicles, enabling their large-scale adoption.

Rational design of PGM-spinel oxide catalysts for enhanced methane conversion

ACS Fall 2021

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