Catalytic Kinetics of Different Types of Surface Atoms on Shaped Pd Nanocrystals

Dynamics of chemical reactions on single nanocatalysts with heterogeneous active sites

Modern chemical science and industries critically depend on the application of various catalytic methods. However, the underlying molecular mechanisms of these processes still remain not fully understood. Recent experimental advances that produced highly-efficient nanoparticle catalysts allowed researchers to obtain more quantitative descriptions, opening the way to clarify the microscopic picture of catalysis. Stimulated by these developments, we present a minimal theoretical model that investigates the effect of heterogeneity in catalytic processes at the single-particle level. Using a discrete-state stochastic framework that accounts for the most relevant chemical transitions, we explicitly evaluated the dynamics of chemical reactions on single heterogeneous nanocatalysts with different types of active sites. It is found that the degree of stochastic noise in nanoparticle catalytic systems depends on several factors that include the heterogeneity of catalytic efficiencies of active sites and distinctions between chemical mechanisms on different active sites. The proposed theoretical approach provides a single-molecule view of heterogeneous catalysis and also suggests possible quantitative routes to clarify some important molecular details of nanocatalysts.

In situ quantitative single-molecule study of site-specific photocatalytic activity and dynamics on ultrathin g-C3N4 nanosheets

Graphitic carbon nitride (g-C₃N₄) has attracted extensive research attention in recent years due to its unique layered structure, facile synthetic route, visible-light-responsive nature, and excellent photocatalytic performance. However, an insightful investigation of site-specific catalytic activities and kinetics on g-C₃N₄ is still warranted. Here, we fabricated ultrathin g-C₃N₄ nanosheets through thermal exfoliation. The optimized sample exhibits a high specific surface area of 307.35 m² g^-1 and a remarkable H₂ generation activity of 2008 μmol h^-1 g^-1 with an apparent quantum efficiency of 4.62% at λ = 420 nm. Single-molecule fluorescence microscopy was applied for the first time to spatially resolve the reaction heterogeneities with nanometer precision (∼10 nm). The catalytic kinetics (i.e., reactant adsorption, conversion, and product dissociation) and temporal activity fluctuations were in situ quantified at individual structural features (i.e., wrinkles, edges, and basal planes) of g-C₃N₄. It was found that the wrinkle and edge exhibited superior photocatalytic activity due to the intrinsic band modulation, which are 20 times and 14.8 times that of the basal plane, respectively. Moreover, due to the steric effect, the basal plane showed the highest adsorption constant and the lowest direct dissociation constant. Density functional theory (DFT) simulations unveiled the adsorption energies of reactant and product molecules on each structure of g-C₃N₄, which support our experimental results. Such investigation would shed more light on the fundamental understanding of site-specific catalytic dynamics on g-C₃N₄, which benefits the rational design of 2D layered materials for efficient solar-to-chemical energy conversion.

Stochastic Kinetics of Nanocatalytic Systems

Catalytic reaction events occurring on the surface of a nanoparticle constitute a complex stochastic process. Although advances in modern single-molecule experiments enable direct measurements of individual catalytic turnover events occurring on a segment of a single nanoparticle, we do not yet know how to measure the number of catalytic sites in each segment or how the catalytic turnover counting statistics and the catalytic turnover time distribution are related to the microscopic dynamics of catalytic reactions. Here, we address these issues by presenting a stochastic kinetics for nanoparticle catalytic systems. We propose a new experimental measure of the number of catalytic sites in terms of the mean and variance of the catalytic event count. By considering three types of nanocatalytic systems, we investigate how the mean, the variance, and the distribution of the catalytic turnover time depend on the catalytic reaction dynamics, the heterogeneity of catalytic activity, and communication among catalytic sites. This work enables accurate quantitative analyses of single-molecule experiments for nanocatalytic systems and enzymes with multiple catalytic sites.

Site-Resolved Cu2 O Catalysis in the Oxidation of CO

The identification of the contribution of different surface sites to the catalytic activity of a catalyst nanoparticle is one of the most challenging issues in the fundamental studies of heterogeneous catalysis. We herein demonstrate an effective strategy of using a series of uniform cubic Cu₂ O nanocrystals with different sizes to identify the intrinsic activity and contributions of face and edge sites in the catalysis of CO oxidation by a combination of reaction kinetics analysis and DFT calculations. Cu₂ O nanocrystals undergo in situ surface oxidation forming CuO thin films during CO oxidation. As the average size of the cubic Cu₂ O nanocrystals decreases from 1029 nm to 34 nm, the dominant active sites contributing to the catalytic activity switch from face sites to edge sites. These results reveal the interplay between the intrinsic catalytic activity and the density of individual types of surface sites on a catalyst nanoparticle in determining their contributions to the catalytic activity.

Revealing the thermodynamics of individual catalytic steps based on temperature-dependent single-particle nanocatalysis

Due to the intrinsic heterogeneity of nanocatalysis, many underlying catalytic details on nanocatalysts are hidden in ensemble-averaged measurements.

Tailoring Copper Nanocrystals towards C2 Products in Electrochemical CO2 Reduction

Favoring the CO2 reduction reaction (CO2RR) over the hydrogen evolution reaction and controlling the selectivity towards multicarbon products are currently major scientific challenges in sustainable energy research. It is known that the morphology of the catalyst can modulate catalytic activity and selectivity, yet this remains a relatively underexplored area in electrochemical CO2 reduction. Here, we exploit the material tunability afforded by colloidal chemistry to establish unambiguous structure/property relations between Cu nanocrystals and their behavior as electrocatalysts for CO2 reduction. Our study reveals a non-monotonic size-dependence of the selectivity in cube-shaped copper nanocrystals. Among 24 nm, 44 nm and 63 nm cubes tested, the cubes with 44 nm edge length exhibited the highest selectivity towards CO2RR (80 %) and faradaic efficiency for ethylene (41 %). Statistical analysis of the surface atom density suggests the key role played by edge sites in CO2RR.