Siphon-Like Effect in Chemical Reactions: Kinetic Basis of Bifunctional OX-ZEO Catalyst for Selective Syngas Conversion to Light Olefins

Despite considerable progress in the oxide-zeolite coupled bifunctional catalyst (OX-ZEO) for ketene-mediated syngas conversion, it is still unclear how the cooperative mechanism between zeolite and oxide enables the selective formation of light olefins and how it is affected by the spatial proximity of OX-ZEO, let alone the rational optimization of the OX-ZEO catalytic system. Herein, we present a diffusion-bridged two-component microkinetic model that incorporates the calculated energetics of the entire reaction network over the ZnCrO_x/MOR catalyst. This model dynamically captures the intricate kinetic behavior of this bifunctional system and quantitatively unravels the siphon-like synergetic mechanism in the selective conversion of syngas to light olefins instead of methane. The zeolite-enhanced selectivity for light olefin can be attributed to overcoming the unfavorable thermodynamic limitation to CH₂CO formation on the oxide via being driven by a more favorable conversion in MOR. Furthermore, our model predicts an inverted U-shaped proximity dependence between two components on modulating the product activity/selectivity; this is due to the kinetic constraint of intermediate transfer at a physical proximity and the unexpected migration of Zn species when two components interact at the bonding level, leading to the formation of Zn[OH]⁺ species that trigger the undesired deep hydrogenation. Importantly, we have proposed a generalized OX-ZEO-based reaction-diffusion coupling kinetic model that essentially quantifies the optimal combination principles of two components. The predictions from our model agree well with the experimentally reported OX-ZEO catalysts, and we propose several new promising combinations of oxides and zeolites (ZnVO_x, Ga/Sc-doped MOR). The theoretical understanding derived from this study could contribute to the rational design of the optimal OX-ZEO catalyst.