Reagent-Triggered Isomerization of Fluxional Cluster Catalyst via Dynamic Coupling

Stability and Reversible Oxidation of Sub-Nanometric Cu5 Metal Clusters: Integrated Experimental Study and Theoretical Modeling

Sub-nanometer metal clusters have special physical and chemical properties, significantly different from those of nanoparticles. However, there is a major concern about their thermal stability and susceptibility to oxidation. In situ X-ray Absorption spectroscopy and Near Ambient Pressure X-ray Photoelectron spectroscopy results reveal that supported Cu5 clusters are resistant to irreversible oxidation at least up to 773 K, even in the presence of 0.15 mbar of oxygen. These experimental findings can be formally described by a theoretical model which combines dispersion-corrected DFT and first principles thermochemistry revealing that most of the adsorbed O2 molecules are transformed into superoxo and peroxo species by an interplay of collective charge transfer within the network of Cu atoms and large amplitude "breathing" motions. A chemical phase diagram for Cu oxidation states of the Cu5 -oxygen system is presented, clearly different from the already known bulk and nano-structured chemistry of Cu.

Dynamical Study of Adsorbate-Induced Restructuring Kinetics in Bimetallic Catalysts Using the PdAu(111) Model System

Dynamic restructuring of bimetallic catalysts plays a crucial role in their catalytic activity and selectivity. In particular, catalyst pretreatment with species such as carbon monoxide and oxygen has been shown to be an effective strategy for tuning the surface composition and morphology. Mechanistic and kinetic understanding of such restructuring is fundamental to the chemistry and engineering of surface active sites but has remained challenging due to the large structural, chemical, and temporal degrees of freedom. Here, we combine time-resolved temperature-programmed infrared reflection absorption spectroscopy, ab initio thermodynamics, and machine-learning molecular dynamics to uncover previously unidentified timescale and kinetic parameters of in situ restructuring in Pd/Au(111), a highly relevant model system for dilute Pd-in-Au nanoparticle catalysts. The key innovation lies in utilizing CO not only as a chemically sensitive probe of surface Pd but also as an agent that induces restructuring of the surface. Upon annealing in vacuum, as-deposited Pd islands became encapsulated by Au and partially dissolved into the subsurface, leaving behind isolated Pd monomers on the surface. Subsequent exposure to 0.1 mbar CO enabled Pd monomers to repopulate the surface up to 373 K, above which complete Pd dissolution occurred by 473 K, with apparent activation energies of 0.14 and 0.48 eV, respectively. These restructuring processes occurred over the span of ∼1000 s at a given temperature. Such a minute-timescale dynamics not only elucidates the fluxional nature of alloy catalysts but also presents an opportunity to fine-tune the surface under moderate temperature and pressure conditions.

Theoretical Perspective on Operando Spectroscopy of Fluxional Nanocatalysts

Improvements in operando spectroscopy have enabled the catalysis community to investigate the dynamic nature of catalysts under operating conditions with increasing detail. Still, the highly dynamic nature of some catalysts, such as fluxional supported subnano clusters, presents a formidable challenge even for the most state-of-the-art techniques. The reason is that such fluxional catalytic interfaces contain a variety of thermally accessible states. Operando spectroscopies used in catalysis generally fall into two categories: ensemble-based techniques, which provide spectra containing the signals of the entire ensemble of states of the catalyst and are not necessarily dominated by the most active species, and localized techniques, which provide atomistic-level information about the dynamics of active sites in a very small area, which might not include the most active species. Combining many different kinds of techniques can provide detailed insight; however, we propose that effective utilization of specific computational techniques and approaches within the fluxionality paradigm can fill the gap and enable atomistic characterization of the most relevant catalytic sites.

Exploring Blob Detection to Determine Atomic Column Positions and Intensities in Time-Resolved TEM Images with Ultra-Low Signal-to-Noise

Spatially resolved in situ transmission electron microscopy (TEM), equipped with direct electron detection systems, is a suitable technique to record information about the atom-scale dynamics with millisecond temporal resolution from materials. However, characterizing dynamics or fluxional behavior requires processing short time exposure images which usually have severely degraded signal-to-noise ratios. The poor signal-to-noise associated with high temporal resolution makes it challenging to determine the position and intensity of atomic columns in materials undergoing structural dynamics. To address this challenge, we propose a noise-robust, processing approach based on blob detection, which has been previously established for identifying objects in images in the community of computer vision. In particular, a blob detection algorithm has been tailored to deal with noisy TEM image series from nanoparticle systems. In the presence of high noise content, our blob detection approach is demonstrated to outperform the results of other algorithms, enabling the determination of atomic column position and its intensity with a higher degree of precision.

Achieving industrial ammonia synthesis rates at near-ambient conditions through modified scaling relations on a confined dual site

The production of ammonia through the Haber-Bosch process is regarded as one of the most important inventions of the 20th century. Despite significant efforts in optimizing the process, it still consumes 1 to 2% of the worldwide annual energy for the high working temperatures and pressures. The design of a catalyst with a high activity at milder conditions represents another challenge for this reaction. Herein, we combine density functional theory and microkinetic modeling to illustrate a strategy to facilitate low-temperature and -pressure ammonia synthesis through modified energy-scaling relationships using a confined dual site. Our results suggest that an ammonia synthesis rate two to three orders of magnitude higher than the commercial Ru catalyst can be achieved under the same reaction conditions with the introduction of confinement. Such strategies will open pathways for the development of catalysts for the Haber-Bosch process that can operate at milder conditions and present more economically viable alternatives to current industrial solutions.

IR Spectroscopic Characterization of H2 Adsorption on Cationic Cun+ (n = 4-7) Clusters

IR spectra of cationic copper clusters Cu_n⁺ (n = 4–7) complexed with hydrogen molecules are recorded via IR multiple-photon dissociation (IRMPD) spectroscopy. To this end, the copper clusters are generated via laser ablation and reacted with H₂ and D₂ in a flow-tube-type reaction channel. The complexes formed are irradiated using IR light provided by the free-electron laser for intracavity experiments (FELICE). The spectra are interpreted by making use of isotope-induced shifts of the vibrational bands and by comparing them to density functional theory calculated spectra for candidate structures. The structural candidates have been obtained from global sampling with the minima hopping method, and spectra are calculated at the semilocal (PBE) and hybrid (PBE0) functional level. The highest-quality spectra have been recorded for [5Cu, 2H/2D]⁺, and we find that the semilocal functional provides better agreement for the lowest-energy isomers. The interaction of hydrogen with the copper clusters strongly depends on their size. Binding energies are largest for Cu₅⁺, which goes hand in hand with the observed predominantly dissociative adsorption. Due to smaller binding energies for dissociated H₂ and D₂ for Cu₄⁺, also a significant amount of molecular adsorption is observed as to be expected according to the Evans–Polanyi principle. This is confirmed by transition-state calculations for Cu₄⁺ and Cu₅⁺, which show that hydrogen dissociation is not hindered by an endothermic reaction barrier for Cu₅⁺ and by a slightly endothermic barrier for Cu₄⁺. For Cu₆⁺ and Cu₇⁺, it was difficult to draw clear conclusions because the IR spectra could not be unambiguously assigned to structures.

Atomic Scale Characterization of Fluxional Cation Behavior on Nanoparticle Surfaces: Probing Oxygen Vacancy Creation/Annihilation at Surface Sites

Oxygen vacancy creation and annihilation are key processes in nonstoichiometric oxides such as CeO₂. The oxygen vacancy creation and annihilation rates on an oxide's surface partly govern its ability to exchange oxygen with the ambient environment, which is critical for a number of applications including energy technologies, environmental pollutant remediation, and chemical synthesis. Experimental methods to probe and correlate local oxygen vacancy reaction rates with atomic-level structural heterogeneities would provide significant information for the rational design and control of surface functionality; however, such methods have been unavailable to date. Here, we characterize picoscale fluxional behavior in cations using time-resolved in situ aberration-corrected transmission electron microscopy to locate atomic-level variations in oxygen vacancy creation and annihilation rates on oxide nanoparticle surfaces. Low coordination number sites such as steps and edges, as well as locally strained sites, exhibited the greatest number of cation displacements, implying enhanced surface oxygen vacancy activity at these sites. The approach has potential applications to a much wider class of materials and catalysis problems involving surface and interfacial transport functionalities.

Theoretical insights into C-H bond activation of methane by transition metal clusters: the role of anharmonic effects

In heterogeneous catalysis, the determination of active phases has been a long-standing challenge, as materials' properties change under operational conditions (i.e. temperature (T) and pressure (p) in an atmosphere of reactive molecules). As a first step towards materials design for methane activation, we study the T and p dependence of the composition, structure, and stability of metal oxide clusters in a reactive atmosphere at thermodynamic equilibrium using a prototypical model catalyst having wide practical applications: free transition metal (Ni) clusters in a combined oxygen and methane atmosphere. A robust methodological approach is employed, where the starting point is systematic scanning of the potential energy surface (PES) to obtain the global minimum structures using a massively parallel cascade genetic algorithm (cGA) at the hybrid density functional level. The low energy clusters are further analyzed to estimate their thermodynamic stability at realistic T, p O2 and p CH4 using ab initio atomistic thermodynamics (aiAT). To incorporate the anharmonicity in the vibrational free energy contribution to the configurational entropy, we evaluate the excess free energy of the clusters numerically by a thermodynamic integration method with ab initio molecular dynamics (aiMD) simulation inputs. By analyzing a large dataset, we show that the conventional harmonic approximation miserably fails for this class of materials, and capturing the anharmonic effects on the vibration free energy contribution is indispensable. The latter has a significant impact on detecting the activation of the C-H bond, while the harmonic infrared spectrum fails to capture this, due to the wrong prediction of the vibrational modes.

Importance learning estimator for the site-averaged turnover frequency of a disordered solid catalyst

For disordered catalysts such as atomically dispersed "single-atom" metals on amorphous silica, the active sites inherit different properties from their quenched-disordered local environments. The observed kinetics are site-averages, typically dominated by a small fraction of highly active sites. Standard sampling methods require expensive ab initio calculations at an intractable number of sites to converge on the site-averaged kinetics. We present a new method that efficiently estimates the site-averaged turnover frequency (TOF). The new estimator uses the same importance learning algorithm [Vandervelden et al., React. Chem. Eng. 5, 77 (2020)] that we previously used to compute the site-averaged activation energy. We demonstrate the method by computing the site-averaged TOF for a simple disordered lattice model of an amorphous catalyst. The results show that with the importance learning algorithm, the site-averaged TOF and activation energy can now be obtained concurrently with orders of magnitude reduction in required ab initio calculations.

Nanocluster and single-atom catalysts for thermocatalytic conversion of CO and CO2

We highlight different aspects of single-atom and nanocluster catalysts for CO₂ reduction and CO oxidation, including synthesis, dynamic restructuring, and trends in activity and selectivity.

An approach to calculate the free energy changes of surface reactions using free energy decomposition on ab initio brute-force molecular dynamics trajectories

To understand the mechanisms and kinetics of catalytic reactions in heterogeneous catalysis, ab initio molecular dynamics is one of the powerful methods used to explore the free energy surface (FES) of surface elementary steps.