Theoretical search for characteristic atoms in supported gold nanoparticles: a large-scale DFT study

The size and site dependences of atomic and electronic structures in isolated and supported gold nanoparticles have been investigated using large-scale density functional theory (DFT) calculations using multi-site support functions. The effects of the substrate on nanoparticles with diameters of 2 nm and several different shapes have been examined. First, isolated gold nanoparticles with diameters of 0.6 nm (13 atoms) to 4.5 nm (2057 atoms), which have comparable sizes to nanoparticles used in experiments, were considered. To analyse huge amounts of data obtained from large-scale DFT calculations, we performed principal component analysis (PCA), which helps systematically and efficiently clarify the electronic structures of large nanoparticles. The PCA results reveal the site dependence of the electronic structures. Notably, the atoms in the surface and subsurface have different electronic structures to those located in the inner layers, especially at the vertexes of the particles. The convergence of local electronic structures with respect to the particle size has also been demonstrated. For supported nanoparticles, PCA helps indicate which atoms are affected, and how much, by the substrate. The correlation between the PCA results and site dependence of reaction activity is also discussed herein.

Accelerated Lignocellulosic Molecule Adsorption Structure Determination

Here, we present a study combining Bayesian optimization structural inference with the machine learning interatomic potential Neural Equivariant Interatomic Potential (NequIP) to accelerate and enable the study of the adsorption of the conformationally flexible lignocellulosic molecules β-d-xylose and 1,4-β-d-xylotetraose on a copper surface. The number of structure evaluations needed to map out the relevant potential energy surfaces are reduced by Bayesian optimization, while NequIP minimizes the time spent on each evaluation, ultimately resulting in cost-efficient and reliable sampling of large systems and configurational spaces. Although the applicability of Bayesian optimization for the conformational analysis of the more flexible xylotetraose molecule is restricted by the sample complexity bottleneck, the latter can be effectively bypassed with external conformer search tools, such as the Conformer-Rotamer Ensemble Sampling Tool, facilitating the subsequent lower-dimensional global minimum adsorption structure determination. Finally, we demonstrate the applicability of the described approach to find adsorption structures practically equivalent to the density functional theory counterparts at a fraction of the computational cost.

Investigation of the electronic and optical properties of bilayer CdS as a gas sensor: first-principles calculations

We utilised first-principles computations based on density functional theory to investigate the optical and electronic properties of bilayer CdS before and after the adsorption of gas molecules. Initially, we examined four candidate adsorption sites to determine the best site for adsorbing CO, CO2, SO2, H2S, and SO. In order to achieve the optimal adsorption configurations, we analysed the adsorption energy, distance, and total charge. Our findings reveal that the CdS bilayer forms a unique connection between the O and Cd atoms, as well as the S and Cd atoms, which renders it sensitive to SO2, H2S, and SO through chemical adsorption, and CO and CO2 through strong physical adsorption. The adsorption of gas molecules enhances the optical properties of the CdS bilayer. Consequently, the CdS bilayer proves to be a highly efficient gas sensor for SO2, H2S, and SO gases.

Preventing Premature Convergence in Evolutionary Structure Determination of Complex Molecular Systems: Demonstration in Few-Nanometer-Sized TiCl4-Capped MgCl2 Nanoplates

The combination of genetic algorithm-based global search and local geometry optimization enables nonempirical structure determination for complex materials such as practical solid catalysts. However, premature convergence in the genetic algorithm hinders the determination of the global minimum for complicated molecular systems. Here, we implemented a distributed genetic algorithm based on the migration from a structure database for avoiding the premature convergence, and thus we realized the structure determination for TiCl₄-capped MgCl₂ nanoplates with experimentally consistent sizes. The obtained molecular models are featured with a realistic size and nonideal surfaces, representing actual primary particles of catalysts.

Influence of ionic liquids on the electronic environment of atomically dispersed Ir on (MgO) (100)

Recently, ionic liquids (ILs) have been used as ligands for single-site Ir(CO)2 complexes bound to metal-oxide supports because of their electron-donor/acceptor capacities. The combined effects of supports and ILs as...

IrO_{2} Surface Complexions Identified through Machine Learning and Surface Investigations

A Gaussian approximation potential was trained using density-functional theory data to enable a global geometry optimization of low-index rutile IrO_{2} facets through simulated annealing. Ab initio thermodynamics identifies (101) and (111) (1×1) terminations competitive with (110) in reducing environments. Experiments on single crystals find that (101) facets dominate and exhibit the theoretically predicted (1×1) periodicity and x-ray photoelectron spectroscopy core-level shifts. The obtained structures are analogous to the complexions discussed in the context of ceramic battery materials.

NWPEsSe: An Adaptive-Learning Global Optimization Algorithm for Nanosized Cluster Systems

Global optimization constitutes an important and fundamental problem in theoretical studies in many chemical fields, such as catalysis, materials, or separations problems. In this paper, a novel algorithm has been developed for the global optimization of large systems including neat and ligated clusters in the gas phase and supported clusters in periodic boundary conditions. The method is based on an updated artificial bee colony (ABC) algorithm method, that allows for adaptive-learning during the search process. The new algorithm is tested against four classes of systems of diverse chemical nature: gas phase Au₅₅, ligated Au₈²⁺, Au₈ supported on graphene oxide and defected rutile, and a large cluster assembly [Co₆Te₈(PEt₃)₆][C₆₀]_n, with sizes ranging between 1 and 3 nm and containing up to 1300 atoms. Reliable global minima (GMs) are obtained for all cases, either confirming published data or reporting new lower energy structures. The algorithm and interface to other codes in the form of an independent program, Northwest Potential Energy Search Engine (NWPEsSe), is freely available, and it provides a powerful and efficient approach for global optimization of nanosized cluster systems.

Non-covalent Interactions and Charge Transfer between Propene and Neutral Yttrium-Doped and Pure Gold Clusters

The dopant and size-dependent propene adsorption on neutral gold (Aun ) and yttrium-doped gold (Aun-1 Y) clusters in the n=5-15 size range are investigated, combining mass spectrometry and gas phase reactions in a low-pressure collision cell and density functional theory calculations. The adsorption energies, extracted from the experimental data using an RRKM analysis, show a similar size dependence as the quantum chemical results and are in the range of ≈0.6-1.2 eV. Yttrium doping significantly alters the propene adsorption energies for n=5, 12 and 13. Chemical bonding and energy decomposition analysis showed that there is no covalent bond between the cluster and propene, and that charge transfer and other non-covalent interactions are dominant. The natural charges, Wiberg bond indices, and the importance of charge transfer all support an electron donation/back-donation mechanism for the adsorption. Yttrium plays a significant role not only in the propene binding energy, but also in the chemical bonding in the cluster-propene adduct. Propene preferentially binds to yttrium in small clusters (n<10), and to a gold atom at larger sizes. Besides charge transfer, relaxation also plays an important role, illustrating the non-local effect of the yttrium dopant. It is shown that the frontier molecular orbitals of the clusters determine the chemical bonding, in line with the molecular-like electronic structure of metal clusters.

Altering CO binding on gold cluster cations by Pd-doping

The introduction of dopant atoms into metal nanoparticles is an effective way to control the interaction with adsorbate molecules and is important in many catalytic processes. In this work, experimental and theoretical evidence of the influence of Pd doping on the bonding between small cationic AuN+ clusters and CO is presented. The CO adsorption is studied by combining low-pressure collision cell reactivity and infrared multiple photon dissociation spectroscopy experiments with density functional theory calculations. Measured dissociation rates of cluster-CO complexes (N ≤ 21) allow the estimation of cluster-CO binding energies, showing that Pd doping increases the CO adsorption energy to an extent that is size-dependent. These trends are reproduced by theoretical calculations up to N = 13. In agreement with theory, measurements of the C-O vibrational frequency suggest that for the doped PdAuN-1+ (N = 3-5, 11) clusters, CO adsorbs on an Au atom, while for N = 6-10 and N = 12-14, CO interacts directly with the Pd dopant. A pronounced red-shifting of the C-O vibrational frequency is observed when CO interacts directly with the Pd dopant, indicating a significant back-donation of electron charge from Pd to CO. In contrast, the blue-shifted frequencies, observed when CO interacts with an Au atom, indicate that σ-donation dominates the Au-CO interaction. Studying such systems at the sub-nanometre scale enables a fundamental comprehension of the interactions between adsorbates, dopants and the host (Au) species at the atomic level.

Physico-Chemical Insights into Gas-Phase and Oxide-Supported Sub-Nanometre AuCu Clusters

Catalysis by AuCu nanoclusters is a promising scientific field. However, our fundamental understanding of the underlying mechanisms of mixing in AuCu clusters at the sub-nanometre scale and their physico-chemical properties in both the gas-phase and on oxide supports is limited. We have identified the global minima of gas-phase and MgO(100)-supported AuCu clusters with 3–10 atoms using the Mexican Enhanced Genetic Algorithm coupled with density functional theory. Au and Cu adatoms and supported dimers have been also simulated at the same level of theory. The most stable composition, as calculated from mixing and binding energies, is obtained when the Cu proportion is close to 50%. The structures of the most stable free AuCu clusters exhibit Cu-core/Au-shell segregation. On the MgO surface however, there is a preference for Cu atoms to lie at the cluster-substrate interface. Due to the interplay between the number of interfacial Cu atoms and surface-induced cluster rearrangement, on the MgO surface 3D structures become more stable than 2D structures. The O-site of MgO surface is found to be the most favourable adsorption site for both metals. All dimers favour vertical (V) configurations on the surface and their adsorption energies are in the order: AuCu < CuCu < AuAu < AuCu (where the underlined atom is bound to the O-site). For both adatoms and AuCu dimers, adsorption via Cu is more favourable than Au-adsorbed configurations, but, this disagrees with the ordering for the pure dimers due to a combination of electron transfer and the metal-on-top effect. Binding energy (and second difference) and HOMO-LUMO gap calculations show that even-atom (even-electron) clusters are more stable than the neighbouring odd-atom (odd- electron) clusters, which is expected for closed- and open-shell systems. Supporting AuCu clusters on the MgO(100) surface decreases the charge transfer between Au and Cu atoms calculated in free clusters. The results of this study may serve as a foundation for designing better AuCu catalysts.

Structural properties of sub-nanometer metallic clusters

At the nanoscale, the investigation of structural features becomes fundamental as we can establish relationships between cluster geometries and their physicochemical properties. The peculiarity lies in the variety of shapes often unusual and far from any geometrical and crystallographic intuition clusters can assume. In this respect, we should treat and consider nanoparticles as a new form of matter. Nanoparticle structures depend on their size, chemical composition, ordering, as well as external conditions e.g. synthesis method, pressure, temperature, support. On top of that, at finite temperatures nanoparticles can fluctuate among different structures, opening new and exciting horizons for the design of optimal nanoparticles for advanced applications. This article aims to overview geometrical features of transition metal clusters and of their various rearrangements.

Stability of AumAgn (m + n = 1-6) clusters supported on a F-center MgO(100) surface

A theoretical study has been performed for deposited AumAgn (m + n = 1-6) clusters. The combined use of the Mexican Enhanced Genetic Algorithm (MEGA) and Density Functional Theory (DFT) calculations allows us to explore the potential energy surface and therefore, find the global minimum configuration for each composition. We have performed calculations of clusters deposited on defects (oxygen vacancies) known as F centers on MgO (100) surfaces. Our results show interesting differences in the geometries of the clusters upon deposition and as a consequence in their electronic properties. The combination of two metals with different electronegativities creates an inhomogeneous charge distribution on their exposed surface producing good conditions for a catalytic process to take place.

Effects of the cooperative interaction on the diffusion of hydrogen on MgO(100)

Understanding hydrogen diffusion is important for applications such as hydrogen storage and spillover materials. On semiconductors, where paired electron acceptors and donors stabilize each other, the hydrogen diffusion depends on the number of adsorbed fragments. Using density functional theory, we investigate the effects of preadsorbed hydrogens on activation energy and reaction path for hydrogen diffusion on MgO(100): the presence of an unpaired hydrogen causes a diffusion, on O-sites, above the surface with a lower activation energy compared to the case of paired hydrogens where the diffusion distorts the surface. This effect is missing for diffusion on Mg-sites.