Genetic algorithm aided density functional theory simulations unravel the kinetic nature of Au(100) in catalytic CO oxidation

Unveiling the Au Surface Reconstruction in a CO Environment by Surface Dynamics and Ab Initio Thermodynamics

Surface reconstruction changes the atomic configuration of the metal surface and thus alters its intrinsic physical and chemical properties. Recent in situ experiments have shown a variety of surface reconstructions under reaction conditions, but how to effectively predict and characterize these structures remains challenging. Herein, we combine a DFT-based kinetic Monte Carlo simulation method and ab initio thermodynamics to explore the low-energy configurations of metal surface reconstructions, which takes the surface dynamics under the reactive environment into account. We systematically simulate 13 Au surfaces ((100), (110), (111), (210), (211), (221), (310), (311), (320), (321), (322), (331), and (332)) in the CO environment and identify 19 candidate reconstruction patterns driven by CO adsorption. The breakup of the original surfaces is attributed to the lateral interactions among the nearest-neighboring adsorbates. This work provides an efficient approach to unveil the reconstructed metal surface structures in reactive environments for guiding the experiments.

Role of composition and texture on bifunctional catalytic performance of extruded Au–Cu alloys

Extruded Au–Cu alloys can be used as bifunctional catalysts for the electro-oxidation of CH3OH and HCOOH, and their catalytic activities can be improved based on alloying and appropriate texture.

Dynamics of Heterogeneous Catalytic Processes at Operando Conditions

The rational design of high-performance catalysts is hindered by the lack of knowledge of the structures of active sites and the reaction pathways under reaction conditions, which can be ideally addressed by an in situ/operando characterization. Besides the experimental insights, a theoretical investigation that simulates reaction conditions-so-called operando modeling-is necessary for a plausible understanding of a working catalyst system at the atomic scale. However, there is still a huge gap between the current widely used computational model and the concept of operando modeling, which should be achieved through multiscale computational modeling. This Perspective describes various modeling approaches and machine learning techniques that step toward operando modeling, followed by selected experimental examples that present an operando understanding in the thermo- and electrocatalytic processes. At last, the remaining challenges in this area are outlined.

Facet-selective charge separation in two-dimensional bismuth-based photocatalysts

In this review, we summarize recent advances in the facet design of bismuth-based single-crystal plates based on facet-dependent charge separation for photocatalytic reactions, and the manipulation of the spatial charge separation is highlighted.