Dynamic structural disorder in supported nanoscale catalysts

Ensembles of Metastable States Govern Heterogeneous Catalysis on Dynamic Interfaces

Heterogeneous catalysis is at the heart of the chemical industry. Being able to tune and design efficient catalysts for processes of interest is of the utmost importance, and for this, a molecular-level understanding of heterogeneous catalysts is the first step and indeed a prime focus of modern catalysis research. For a long time, the single most thermodynamically stable structure of the catalytic interface attained under the reaction conditions had been envisioned as the reactive phase. However, some catalytic interfaces continue to undergo structural dynamics in the steady state, triggered by high temperatures and pressures and binding and changing reagents. Among particularly dynamic interfaces are such widely used catalysts as crystalline and amorphous surfaced supporting (sub)nanometallic clusters. Recently, it became clear that this dynamic fluxionality causes the supported clusters to populate many distinct structural and stoichiometric states under catalytic conditions. Hence, the catalytic interface should be viewed as an evolving statistical ensemble of many structures (rather than one structure). Every member in the ensemble contributes to the properties of the catalyst differently, in proportion to its probability of being populated. This new notion flips the established paradigm and calls for a new theory, new modeling approaches, operando measurements, and updated design strategies. The statistical ensemble nature of surface-supported subnanocluster catalysts can be exemplified by oxide-supported and adsorbate-covered Pt, Pd, Cu, and CuPd clusters, which are catalytic toward oxidative and nonoxidative dehydrogenation. They have access to a variety of 3D and quasi-2D shapes. The compositions of their thermal ensembles are dependent on the cluster size, leading to size-specific catalytic activities and the famous "every atom counts" phenomenon. The support and adsorbates affect catalyst structures, and the state of the reacting species causes the ensemble to change in every reaction intermediate. The most stable member of the ensemble dominates the thermodynamic properties of the corresponding intermediate, whereas the kinetics can be determined by more active but less populated metastable catalyst states, and that suggests that many earlier studies might have overlooked the actual active sites. Both effects depend on the relative time scales of catalyst restructuring and reaction dynamics. The catalyst may routinely operate off-equilibrium. Ensemble phenomena lead to surprising exceptions from established rules of catalysis, such as scaling relations and Arrhenius behavior. Catalyst deactivation is also an ensemble property, and its extent of mitigation can be predicted through the new paradigm. These findings were enabled by advances in theory, such as global optimization and subsequent utilization of multiple local minima and pathways sampling as well as operando catalyst characterization. The fact that the per-site and per-species resolution is needed for the description and prediction of catalyst properties gives theory the central role in catalysis research, as most experiments provide ensemble-average information and cannot detect the crucial minority species that may be responsible for the catalytic activity.

Solving the Structure and Dynamics of Metal Nanoparticles by Combining X-Ray Absorption Fine Structure Spectroscopy and Atomistic Structure Simulations

Extended X-ray absorption fine structure (EXAFS) spectroscopy is a premiere method for analysis of the structure and structural transformation of nanoparticles. Extraction of analytical information about the three-dimensional structure and dynamics of metal-metal bonds from EXAFS spectra requires special care due to their markedly non-bulk-like character. In recent decades, significant progress has been made in the first-principles modeling of structure and properties of nanoparticles. In this review, we summarize new approaches for EXAFS data analysis that incorporate particle structure modeling into the process of structural refinement.

Anomalous Structural Disorder in Supported Pt Nanoparticles

Supported Pt nanocatalysts generally exhibit anomalous behavior, including negative thermal expansion and large structural disorder. Finite temperature DFT/MD simulations reproduce these properties, showing that they are largely explained by a combination of thermal vibrations and low-frequency disorder. We show here that a full interpretation is more complex and that the DFT/MD mean-square relative displacements (MSRD) can be further separated into vibrational disorder, "dynamic structural disorder" (DSD), and long-time equilibrium fluctuations of the structure dubbed "anomalous structural disorder" (ASD). We find that the vibrational and DSD components behave normally, increasing linearly with temperature while the ASD decreases, reflecting the evolution of mean nanoparticle geometry. As a consequence the usual procedure of fitting the MSRD to normal vibrations plus temperature-independent static disorder results in unphysical bond strengths and Grüneisen parameters.

Probing the Limits of Conventional Extended X-ray Absorption Fine Structure Analysis Using Thiolated Gold Nanoparticles

We present a method for quantifying the accuracy of extended X-ray absorption fine structure (EXAFS) fitting models. As a test system, we consider the structure of bare Au147 nanoparticles as well as particles bound with thiol ligands, which are used to systematically vary disorder in the atomic structure of the nanoparticles. The accuracy of the fitting model is determined by comparing two distributions of bond lengths: (1) a direct average over a molecular dynamics (MD) trajectory using forces and energies from density functional theory (DFT) and (2) a fit to the theoretical EXAFS spectra generated from that same trajectory. Both harmonic and quasi-harmonic EXAFS fitting models are used to characterize the first-shell Au-Au bond length distribution. The harmonic model is found to significantly underestimate the coordination number, disorder, and bond length. The quasi-harmonic model, which includes the third cumulant of the first-shell bond length distribution, yields accurate bond lengths, but incorrectly predicts a decrease in particle size and little change in the disorder with increasing thiol ligands. A direct analysis of the MD data shows that the particle surfaces become much more disordered with ligand binding, and the high disorder is incorrectly interpreted by the EXAFS fitting models. Our DFT calculations compare well with experimental EXAFS measurements of Au nanoparticles, synthesized using a dendrimer encapsulation technique, showing that systematic errors in EXAFS fitting models apply to nanoparticles 1-2 nm in size. Finally we show that a combination of experimental EXAFS analysis with candidate models from DFT is a promising strategy for a more accurate determination of nanoparticle structures.