The collective ensemble properties of nanoparticles (NPs) deposited on supported catalysts, defined by design parameters such as the NP loading, dispersion, and inter-NP distance, have a pronounced impact on catalytic activity, selectivity, and stability. Traditional preparative methods of precipitation or impregnation entail nucleating NPs on the support. Thereby, a higher metal precursor concentration increases the NP loading but also yields larger NPs, which disguises the direct effects of NP size and inter-NP distance on catalysis. Herein, we use raspberry-colloid templating (RCT) to partially embed pre-formed dilute Pd-in-Au NPs within a macroporous SiO<sub>2</sub> support, ensuring a preserved NP size distribution during preparation and catalysis. By varying the NP loading in the RCT fabrication process, the average inter-NP distance can be altered without modifying the NP size distribution. This enables the independent investigation of the effect of inter-NP distance on catalysis, as exemplified for the liquid phase hydrogenation of benzaldehyde to benzyl alcohol. As the inter-NP distance was reduced, an increased fraction of benzyl alcohol produced re-adsorbed to an adjacent NP instead of diffusing into the bulk liquid, reacting further to form toluene and reducing benzyl alcohol yield. These findings suggest that mesoscale descriptors, such as inter-NP distance and re-adsorption of intermediates, can play a critical role in product selectivity.

Interparticle distance influences catalytic selectivity in benzaldehyde hydrogenation

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