Near-Ambient Pressure XPS and MS Study of CO Oxidation over Model Pd-Au/HOPG Catalysts: The Effect of the Metal Ratio

In this study, the dependence of the catalytic activity of highly oriented pyrolytic graphite (HOPG)-supported bimetallic Pd-Au catalysts towards the CO oxidation based on the Pd/Au atomic ratio was investigated. The activities of two model catalysts differing from each other in the initial Pd/Au atomic ratios appeared as distinctly different in terms of their ignition temperatures. More specifically, the PdAu-2 sample with a lower Pd/Au surface ratio (~0.75) was already active at temperatures less than 150 °C, while the PdAu-1 sample with a higher Pd/Au surface ratio (~1.0) became active only at temperatures above 200 °C. NAP XPS revealed that the exposure of the catalysts to a reaction mixture at RT induces the palladium surface segregation accompanied by an enrichment of the near-surface regions of the two-component Pd-Au alloy nanoparticles with Pd due to adsorption of CO on palladium atoms. The segregation extent depends on the initial Pd/Au surface ratio. The difference in activity between these two catalysts is determined by the presence or higher concentration of specific active Pd sites on the surface of bimetallic particles, i.e., by the ensemble effect. Upon cooling the sample down to room temperature, the reverse redistribution of the atomic composition within near-surface regions occurs, which switches the catalyst back into inactive state. This observation strongly suggests that the optimum active sites emerge under reaction conditions exclusively, involving both high temperature and a reactive atmosphere.

Asymmetric azide-alkyne Huisgen cycloaddition on chiral metal surfaces

Achieving fundamental understanding of enantioselective heterogeneous synthesis is marred by the permanent presence of multitudinous arrangements of catalytically active sites in real catalysts. In this study, we address this issue by using structurally comparatively simple, well-defined, and chiral intermetallic PdGa{111} surfaces as catalytic substrates. We demonstrate the impact of chirality transfer and ensemble effect for the thermally activated azide-alkyne Huisgen cycloaddition between 3-(4-azidophenyl)propionic acid and 9-ethynylphenanthrene on these threefold symmetric intermetallic surfaces under ultrahigh vacuum conditions. Specifically, we encounter a dominating ensemble effect for this reaction as on the Pd3-terminated PdGa{111} surfaces no stable heterocoupled structures are created, while on the Pd1-terminated PdGa{111} surfaces, the cycloaddition proceeds regioselectively. Moreover, we observe chirality transfer from the substrate to the reaction products, as they are formed enantioselectively on the Pd1-terminated PdGa{111} surfaces. Our results evidence a determinant ensemble effect and the immense potential of PdGa as asymmetric heterogeneous catalyst.

Groundwater recharge potential zonation using an ensemble of machine learning and bivariate statistical models

Many regions in Iran are currently experience water crisis, largely driven by frequent droughts and expanding agricultural land combined with over abstraction of groundwater. Therefore, it is extremely important to identify potential groundwater recharge (GWR) zones to help in prevent water scarcity. The key objective of this research is to applying different scenarios for GWR potential mapping by means of a classifier ensemble approach, namely a combination of Maximum Entropy (ME) and Frequency Ratio (FR) models in a semi-arid mountainous, Marboreh Watershed of Iran. To consider the ensemble effect of these models, 15 input layers were generated and used in two models and then the models were combined in seven scenarios. According to marginal response curves (MRCs) and the Jackknife technique, quaternary formations (Qft1 and Qft2) of lithology, sandy-clay-loam (Sa. Cl. L) class of soil, 0–4% class of slope, and agriculture & rangeland classes of land use, offered the highest percolation potential. Results of the FR model showed that the highest weight belonged to Qft1 rocks and Sa. Cl. L textures. Seven scenarios were used for GWR potential maps by different ensembles based on basic mathematical operations. Correctly Classified Instances (CCI), and the AUC indices were applied to validate model predictions. The validation indices showed that scenarios 5 had the best performance. The combination of models by different ensemble scenarios enhances the efficiency of these models. This study serves as a basis for future investigations and provides useful information for prediction of sites with groundwater recharge potential through combination of state-of-the-art statistical and machine learning models. The proposed ensemble model reduced the machine learning and statistical models’ limitations gaps and promoted the accuracy of the model where combining, especially for data-scarce areas. The results of present study can be used for the GWR potential mapping, land use planning, and groundwater development plans.

A first-principles understanding of the CO-assisted NO reduction on the IrRu/Al2O3 catalyst under O2-rich conditions

The IrRu alloy offered optimal energetics for NO reduction by CO. The ensemble effect plays a key role in promoting the reactivity of the IrRu alloy. Making the IrRu surface alloy is better for CO-SCR than forming an alloy over the bulk structure.