Acid-site reactivity in zeolite catalysis: alkene-methanol reactions

Simulated turnover frequency for the methanol−alkene reactions as a function of ΔHNH3 for zeotype materials with the CHA framework topology. (A) Total rate of the reaction of methanol with ethene (black line), propene (red line) and isobutene (blue line). The calculated value of ΔHNH3 for Si-AlPO-34 of −98 kJ/mol is highlighted. (B−D) Rate of the concerted (red lines) and stepwise (blue lines) mechanism along with the total rate (concerted + stepwise mechanism, dashed black lines) for ethene (B), propene (C), and isobutene (D) methylation.

In-silico catalyst design is one of the ultimate goals in the field of heterogeneous catalysis, as such a design can potentially speed up the discovery of new catalytic materials tremendously. The design strategy is usually based on identifying key descriptors that determine the catalytic activity and selectivity of materials, allowing for fast screening of new catalysts. Recently, researchers at SUNCAT reported the first step towards a descriptor-based approach for solid-acid catalysis (J. Phys. Chem. Lett. 2014, 5, 1516–1521). The key property is the reactivity of Brønsted acid sites; how readily the sites donate a proton to and stabilize resulting positively charged transition states and intermediates. The approach was illustrated for the propene-methanol reaction in acidic zeotype catalysts, quantifying the acid-site reactivity through the ammonia heat of adsorption, ∆HNH3.

Now the descriptor-based approach has been extended to reactions between methanol and alkenes of different substitution and size. The researchers established scaling relations between transition state energies and the reactivity descriptor ∆HNH3. Employing the scaling relations in micro-kinetic modeling, it was possible to establish a quantitative relation between reaction rate and acid-site reactivity. This allows screening for improved zeotype catalysts through ∆HNH3, but also to investigate acid-site reactivity and alkene size influence the preferred reaction pathway. The promising results indicate that the descriptor-based approach can potentially be extended to other reactions and classes of solid acid catalysts.