Surface‐supported cluster catalysis: Ensembles of metastable states run the show

Abstract

It has recently been shown that the dynamic behavior of surface‐supported nanocluster catalysts in realistic reaction conditions defies conventional models used in catalysis. This opens new doors in catalysis by giving more leverage in catalyst design, but also requires a major revision of the understanding of how dynamic heterogeneous catalytic interfaces operate, as well as of the computational approaches of catalyst modeling, and experimental methods of catalyst characterization. Major aspects of the new paradigm include the collective action of many catalyst states that form a statistical ensemble in reaction conditions, the catalytic activity and selectivity being driven by rare and metastable catalyst states, reaction thermodynamics and kinetics being controlled by different states of the catalyst, broken scaling relationships, non‐Arrhenius behaviors, and catalyst dynamic restructuring being an essential part of the reaction mechanism. For computation, this complexity means the departure from the standard density functional theory calculations of reaction mechanisms on a single catalyst structure. For experiment, it calls for the development of operando characterization tools with the per‐site resolution and the ability to find the minority sites that govern the catalytic activity. For catalyst design, the goal becomes the creation of the catalyst state (geometric and electronic) that might not be present in the as‐prepared catalyst, but would develop in the reaction conditions and would have the desired activity then. While cluster catalysts are the most dramatic in their dynamic fluxionality, other amorphous interfaces also exhibit some of it, and thus are also subject to similar paradigm revision. This article is categorized under: Structure and Mechanism > Reaction Mechanisms and Catalysis

Interpreting the Operando XANES of Surface-Supported Subnanometer Clusters: When Fluxionality, Oxidation State, and Size Effect Fight

“…The global minimum structure alone is an insufficient model of the catalytic system, as we emphasized in the past. [30][31][32][33][34][35][36][37][38] It is clear from Table S1 and Figure 4 that the position of the risingedge and white line peaks from one isomer to another for the cluster of the same composition can vary up to 4.5 eV and 2.4 eV, respectively (compare Erising-edge of Cu5O3-A and Cu5O5-B, and Ewhiteline of Cu5O5-A and Cu5O5-B). As a result, some of the Cu5O3/UNCD isomers have higher Erisingedge and/or Ewhite-line than some of the Cu5O5/UNCD isomers, while others have the opposite trend.…”

“…However, it has been recently shown that metal clusters in the subnano regime can be highly fluxional, and that an ensemble of many thermally-accessible isomers rather than one stationary global minimum structure is present in the reaction conditions. [30][31][32][33][34][35][36][37][38] These minima may differ not only by shape, but also by chemical composition, such as oxygen content in reaction conditions. This complication inevitably puts in question the usual practice of interpreting the operando XANES spectra for cluster catalysts.…”

Pt8 cluster on alumina under a pressure of hydrogen: Support-dependent reconstruction from first-principles global optimization

“…It has been shown recently that these higher-energy states are critical in determining the properties of cluster catalysts. 34,35,[41][42][43][44] In order to investigate the influence of the hydrogen environment, two different conditions were considered in this work. The first one (T =600 • C and p H 2 =0.1 bar) corresponds to the standard propane dehydrogenation condition, in which hydrogen is co-fed with propane to prevent coke formation.…”

Efficient Global Structure Optimization with a Machine-Learned Surrogate Model

“…In materials science and physical chemistry, the search for optimal structure is a recurring task, e.g. in describing crystalline defects, such as grain boundaries [1] and surface reconstructions [2,3], and in modeling heterogeneous systems such as binary compounds [4,5] and supported nano-particles [6][7][8]. Depending on the search strategy and the complexity of a given problem, many thousands of energy and force evaluations may be required for the structural candidates in the course of the search.…”