Going for Gold(-Standard): Attaining Coupled Cluster Accuracy in Oxide-Supported Nanoclusters

The structure of oxide-supported metal nanoclusters plays an essential role in their sharply enhanced catalytic activity over that of bulk metals. Simulations provide the atomic-scale resolution needed to understand these systems. However, the sensitive mix of metal-metal and metal-support interactions, which govern their structure, puts stringent requirements on the method used, requiring calculations beyond standard density functional theory (DFT). The method of choice is coupled cluster theory [specifically CCSD(T)], but its computational cost has so far prevented its application to these systems. In this work, we showcase two approaches to make CCSD(T) accuracy readily achievable in oxide-supported nanoclusters. First, we leverage the SKZCAM protocol to provide the first benchmarks of oxide-supported nanoclusters, revealing that it is specifically metal-metal interactions that are challenging to capture with DFT. Second, we propose a CCSD(T) correction (ΔCC) to the metal-metal interaction errors in DFT, reaching accuracy comparable to that of the SKZCAM protocol at significantly lower cost. This approach forges a path toward studying larger systems at reliable accuracy, which we highlight by identifying a ground-state structure in agreement with experiments for Au20 on MgO, a challenging system where DFT models have yielded conflicting predictions.

Stability of Single Gold Atoms on Defective and Doped Diamond Surfaces

Polycrystalline boron-doped diamond (BDD) is widely used as a working electrode material in electrochemistry, and its properties, such as its stability, make it an appealing support material for nanostructures in electrocatalytic applications. Recent experiments have shown that electrodeposition can lead to the creation of stable small nanoclusters and even single gold adatoms on the BDD surfaces. We investigate the adsorption energy and kinetic stability of single gold atoms adsorbed onto an atomistic model of BDD surfaces by using density functional theory. The surface model is constructed using hybrid quantum mechanics/molecular mechanics embedding techniques and is based on an oxygen-terminated diamond (110) surface. We use the hybrid quantum mechanics/molecular mechanics method to assess the ability of different density functional approximations to predict the adsorption structure, energy, and barrier for diffusion on pristine and defective surfaces. We find that surface defects (vacancies and surface dopants) strongly anchor adatoms on vacancy sites. We further investigated the thermal stability of gold adatoms, which reveals high barriers associated with lateral diffusion away from the vacancy site. The result provides an explanation for the high stability of experimentally imaged single gold adatoms on BDD and a starting point to investigate the early stages of nucleation during metal surface deposition.

Evaluation of Machine Learning Interatomic Potentials for Gold Nanoparticles-Transferability towards Bulk

We analyse the efficacy of machine learning (ML) interatomic potentials (IP) in modelling gold (Au) nanoparticles. We have explored the transferability of these ML models to larger systems and established simulation times and size thresholds necessary for accurate interatomic potentials. To achieve this, we compared the energies and geometries of large Au nanoclusters using VASP and LAMMPS and gained better understanding of the number of VASP simulation timesteps required to generate ML-IPs that can reproduce the structural properties. We also investigated the minimum atomic size of the training set necessary to construct ML-IPs that accurately replicate the structural properties of large Au nanoclusters, using the LAMMPS-specific heat of the Au147 icosahedral as reference. Our findings suggest that minor adjustments to a potential developed for one system can render it suitable for other systems. These results provide further insight into the development of accurate interatomic potentials for modelling Au nanoparticles through machine learning techniques.

Enhanced stability of sub-nanometric iridium decorated graphitic carbon nitride for H2 production upon hydrous hydrazine decomposition

Stabilizing metal nanoparticles is vital for large scale implementations of supported metal catalysts, particularly for a sustainable transition to clean energy, e.g., H₂ production. In this work, iridium sub-nanometric particles were deposited on commercial graphite and on graphitic carbon nitride by a wet impregnation method to investigate the metal-support interaction during the hydrous hydrazine decomposition reaction. To establish a structure-activity relationship, samples were characterized by transmission electron microscopy and X-ray photoelectron spectroscopy. The catalytic performance of the synthesized materials was evaluated under mild reaction conditions, i.e. 323 K and ambient pressure. The results showed that graphitic carbon nitride (GCN) enhances the stability of Ir nanoparticles compared to graphite, while maintaining remarkable activity and selectivity. Simulation techniques including Genetic Algorithm geometry screening and electronic structure analyses were employed to provide a valuable atomic level understanding of the metal-support interactions. N anchoring sites of GCN were found to minimise the thermodynamic driving force of coalescence, thus improving the catalyst stability, as well as to lead charge redistributions in the cluster improving the resistance to poisoning by decomposition intermediates.

Self-Strained Platinum Clusters with Finite Size: High-Performance Catalysts with CO Tolerance for PEMFCs

Strained platinum-based materials with high performance have been regarded as the most promising electrocatalysts for proton exchange membrane fuel cells (PEMFCs) recently. Herein, self-strained platinum clusters with finite size (about 1 nm) are prepared by a combining liquid- and solid-phase UV irradiation cycle strategy. It started with a fresh H₂PtCl₆ solution irradiated by UV light and then mixed with a graphitized carbon, followed by the dried mixture being subjected to UV light to generate monodispersed Pt clusters on the carbon surface. The obtained platinum clusters feature narrower size distribution and higher loading on carbon, exhibiting significantly improved activity and durability, much higher than that of the-state-of-art commercial Pt/C for the oxygen reduction reaction. More importantly, the self-strained Pt clusters display a surprising CO tolerance, which can be attributed to the unique adaptive lattice compressive strain that triggers an electron enrichment phenomenon for the Pt clusters. Therefore, this stepwise UV irradiation method solves the long-standing problem of both wide size distribution and low loading of metal clusters fabricated by one-step photochemical reduction, providing a potential route for the synthesis of other metal clusters with strained structures.

Discerning phase-matrices for individual nitride inclusions within ultra-high-strength steel: experiment driven DFT investigation

Non-metallic inclusions play a decisive role in the steel's performance. Therefore, their determination and control over their formation are crucial to engineer ultra-high-strength steel. Currently, bare experimental approaches are limited in the identification of non-metallic inclusions within microstructural phases of complex steel matrices. Herein, we performed a density functional theory study on the characteristics of different nitride inclusions as observed in spectro-microscopy studies. As per the simulations, TiN inclusions preferentially formed in the austenite matrix, while the ferrite matrix generally hosts BN inclusions. Furthermore, although the presence of both BN and TiN inclusions in the Fe₃C matrix is possible, their formation is impeded because of the strong inclusion-carbon interactions. The observed regularity in the formation of nitride inclusions in different phases of steel was also confirmed by the comparison of simulated and experimental K-edge XAS spectrum of nitride inclusions. Our work shed the light on the formation of nitride inclusions in different steel matrices and facilitates their further experimental identification.

Adsorption of Transition Metal Catalysts on Carbon Supports: A Theoretical Perspective : Understanding the interaction between catalyst and catalyst supports

Adsorption is a fundamental process which takes place on a catalyst surface before it dissociates, diffuses over the surface and recombines with other adsorbed species to form the final product. Therefore, in theoretical chemistry understanding of the local geometrical and electronic properties of the adsorbed species on the catalyst surface has been a topic of core focus. In this short review we briefly summarise some of the important developments on theoretical studies related to the adsorption properties of transition metal (TM) catalysts on graphene and graphene-related carbon materials. Prior to this, we will present a discussion on various forms of carbon materials used as catalyst supports, which will be followed by a brief discussion of the fundamentals of the density functional theory (DFT).

A TiN@C core–shell support for improving Pt catalyst corrosion resistance

TiN@C composite support with high corrosion resistance improves catalyst durability because of SMSI between the Pt and N site in TiN.

Exploring the materials space in the smallest particle size range: From heterogeneous catalysis to electrocatalysis and photocatalysis

Ultrasmall clusters of subnanometer size can possess unique and even unexpected physical and chemical propensities which make them interesting in various fields of basic science and for potential applications, such...

Unravelling Morphological and Topological Energy Contributions of Metal Nanoparticles

Metal nanoparticles (NPs) are ubiquitous in many fields, from nanotechnology to heterogeneous catalysis, with properties differing from those of single-crystal surfaces and bulks. A key aspect is the size-dependent evolution of NP properties toward the bulk limit, including the adoption of different NP shapes, which may bias the NP stability based on the NP size. Herein, the stability of different Pd_n NPs (n = 10–1504 atoms) considering a myriad of shapes is investigated by first-principles energy optimisation, leading to the determination that icosahedron shapes are the most stable up to a size of ca. 4 nm. In NPs larger than that size, truncated octahedron shapes become more stable, yet a presence of larger {001} facets than the Wulff construction is forecasted due to their increased stability, compared with (001) single-crystal surfaces, and the lower stability of {111} facets, compared with (111) single-crystal surfaces. The NP cohesive energy breakdown in terms of coordination numbers is found to be an excellent quantitative tool of the stability assessment, with mean absolute errors of solely 0.01 eV·atom⁻¹, while a geometry breakdown allows only for a qualitative stability screening.

The Effect of Pristine and Hydroxylated Oxide Surfaces on the Guaiacol HDO Process: A DFT Study

The acid‐base character of oxide supports is crucial for catalytic reactions. In this work, the acid‐base properties of five oxide surfaces common in heterogeneous catalysis were investigated and related to their interaction with monolignol compounds derived from lignin. We have used density functional theory simulations also to understand the role of the surfaces’ hydroxylation state. The results show that moderate hydroxyl coverage on the amphoteric γ‐Al₂O₃ (110) slightly strengthens the oxy‐compounds’ adsorption due to an increase in Lewis acidity. Similarly, low hydroxyl coverage on the reducible TiO₂ (101) enlarges its adsorption capacity by up to 42 % compared with its clean surface. The higher affinity is attributed to the more favourable interaction between the surface‐OH groups and the aromatic rings. Overall, the results indicate that hydroxyl coverage enhances the amphoteric and reducible adsorption capacity towards aromatic species.

Prediction of Co and Ru nanocluster morphology on 2D MoS2 from interaction energies

Layered materials, such as MoS₂, have a wide range of potential applications due to the properties of a single layer, which often differ from the bulk material. They are of particular interest as ultrathin diffusion barriers in semiconductor device interconnects and as supports for low-dimensional metal catalysts. Understanding the interaction between metals and the MoS₂ monolayer is of great importance when selecting systems for specific applications. In previous studies the focus has been largely on the strength of the interaction between a single atom or a nanoparticle of a range of metals, which has created a significant knowledge gap in understanding thin film nucleation on 2D materials. In this paper, we present a density functional theory (DFT) study of the adsorption of small Co and Ru structures, with up to four atoms, on a monolayer of MoS₂. We explore how the metal-substrate and metal-metal interactions contribute to the stability of metal clusters on MoS₂, and how these interactions change in the presence of a sulfur vacancy, to develop insight to allow for a prediction of thin film morphology. The strength of interaction between the metals and MoS₂ is in the order Co > Ru. The competition between metal-substrate and metal-metal interaction allows us to conclude that 2D structures should be preferred for Co on MoS₂, while Ru prefers 3D structures on MoS₂. However, the presence of a sulfur vacancy decreases the metal-metal interaction, indicating that with controlled surface modification 2D Ru structures could be achieved. Based on this understanding, we propose Co on MoS₂ as a suitable candidate for advanced interconnects, while Ru on MoS₂ is more suited to catalysis applications.

Mechanistic study of C–H bond activation by O2 on negatively charged Au clusters: α,β-dehydrogenation of 1-methyl-4-piperidone by supported Au catalysts

Aerobic C–H activation by Au/OMS-2 catalyst is driven by charge transfer from OMS-2 to adsorbed O₂via Au cluster.

Influencing the Electron Density of Nanosized Au Colloids via Immobilization on MgO to Stimulate Surface Reaction Activities

Heterogenization of colloidal gold on MgO is demonstrated to facilitate its catalytic surface reactivity. We show that the electron density on Au influenced by its immobilization on MgO along with the ensued metal-support interaction is one of the key parameters to obtain high activity. As elucidated by X-ray absorption spectroscopic (X-ray photoelectron spectroscopy, X-ray absorption near-edge structure, and extended X-ray absorption fine structure) studies, the presence of well-dispersed nanosized Au on MgO is observed to result in an enhancement in the electron density of Au. The consequence of this electron-rich gold on the catalytic activity is then investigated using the nitroarene reduction as a model reaction with a detailed kinetic study. The kinetic study is an attempt to use a true heterogeneous system rather than the usually studied quasi-homogeneous systems. The results obtained reveal that the Au/MgO catalyst has a surface rate constant of ∼1.39 × 10^-3 mol m^-2 s^-1, which is significantly higher than those of the reported catalysts. While it validates the higher catalytic activity with a TOF of 9456 h^-1 observed for Au/MgO, the increased adsorption constant for 4-nitrophenol on Au/MgO further reflects the efficacy of MgO as the support. This not only allows effective heterogenization of the Au nanoparticles keeping the catalyst stable under the reaction conditions and being reused several times but also renders a capability in reduction of other nitro group-containing substrates. Therefore, the results are believed to be of importance in designing heterogeneous catalysts utilizing the distinctive properties of the nanosized colloids and tuning their surface reactivity as well.

Role of the Support in Gold-Containing Nanoparticles as Heterogeneous Catalysts

In this review, we discuss selected examples from recent literature on the role of the support on directing the nanostructures of Au-based monometallic and bimetallic nanoparticles. The role of support is then discussed in relation to the catalytic properties of Au-based monometallic and bimetallic nanoparticles using different gas phase and liquid phase reactions. The reactions discussed include CO oxidation, aerobic oxidation of monohydric and polyhydric alcohols, selective hydrogenation of alkynes, hydrogenation of nitroaromatics, CO₂ hydrogenation, C–C coupling, and methane oxidation. Only studies where the role of support has been explicitly studied in detail have been selected for discussion. However, the role of support is also examined using examples of reactions involving unsupported metal nanoparticles (i.e., colloidal nanoparticles). It is clear that the support functionality can play a crucial role in tuning the catalytic activity that is observed and that advanced theory and characterization add greatly to our understanding of these fascinating catalysts.