Tetrahedral Clusters Stabilized by Alloying.

A family of nanoclusters of tetrahedral symmetry is proposed. These clusters consist of symmetrically truncated tetrahedra with additional hexagonal islands on the four facets of the starting tetrahedron. The islands are placed in stacking fault positions. The geometric magic numbers of these clusters are derived. Global optimization searches within an atomistic potential model of Pt-Pd show that the tetrahedral structures can be stabilized for intermediate compositions of these nanoalloys, even when they are not the most stable structures of the elemental clusters. These results are also confirmed by density functional theory calculations for the magic sizes 59, 100, and 180. A thermodynamic analysis by the harmonic superposition approximation shows that Pt-Pd tetrahedral nanoalloys can be stable even above room temperature.

Sudden collective atomic rearrangements trigger the growth of defect-free silver icosahedra.

The growth of Ag clusters on amorphous carbon substrates is studied in situ by X-ray scattering experiments, whose final outcome is imaged by electron microscopy. The real-time analysis of the growth process at room temperature shows the formation of a large majority of icosahedral structures by a shell-by-shell growth mode which produces smooth and nearly defect-free structures. Molecular dynamics simulations supported by ab initio calculations reveal that the shell-by-shell mode is possible because of the occurrence of collective displacements which involve the concerted motion of many atoms of the growing shell. These collective processes are a kind of black swan event, as they occur suddenly and rarely, but their occurrence is decisive for the final outcome of the growth. Annealing and ageing experiments show that the as-grown icosahedra are metastable, in agreement with the energetic stability calculations.

Frame-by-frame observations of structure fluctuations in single mass-selected Au clusters using aberration-corrected electron microscopy.

The multi-dimensional potential energy surface (PES) of a nanoparticle, such as a bare cluster of metal atoms, controls both the structure and dynamic behaviour of the particle. These properties are the subject of numerous theoretical simulations. However, quantitative experimental measurements of critical PES parameters are needed to regulate the models employed in the theoretical work. Experimental measurements of parameters are currently few in number, while model parameters taken from bulk systems may not be suitable for nanosystems. Here we describe a new measurement methodology, in which the isomer structures of a single deposited nanocluster are obtained frame-by-frame in an aberration-corrected scanning transmission electron microscope (ac-STEM) in high angle annular dark field (HAADF) mode. Several gold clusters containing 309 ± 15 atoms were analysed individually after deposition from a mass-selected cluster source onto an amorphous carbon film. The main isomers identified are icosahedral (Ih), decahedral (Dh) and face-centred-cubic (fcc) (the bulk structure), alongside many amorphous (glassy) structures. The results, which are broadly consistent with static ac-STEM measurements of an ensemble of such clusters, open the way to dynamic measurements of many different nanoparticles of diverse sizes, shapes and compositions.

Structural transformations in Cu, Ag, and Au metal nanoclusters.

Finite-temperature structures of Cu, Ag, and Au metal nanoclusters are calculated in the entire temperature range from 0 K to melting using a computational methodology that we proposed recently [M. Settem et al., Nanoscale 14, 939 (2022)]. In this method, Harmonic Superposition Approximation (HSA) and Parallel Tempering Molecular Dynamics (PTMD) are combined in a complementary manner. HSA is accurate at low temperatures and fails at higher temperatures. PTMD, on the other hand, effectively samples the high temperature region and melts. This method is used to study the size- and system-dependent competition between various structural motifs of Cu, Ag, and Au nanoclusters in the size range 1-2 nm. Results show that there are mainly three types of structural changes in metal nanoclusters, depending on whether a solid-solid transformation occurs. In the first type, the global minimum is the dominant motif in the entire temperature range. In contrast, when a solid-solid transformation occurs, the global minimum transforms either completely to a different motif or partially, resulting in the co-existence of multiple motifs. Finally, nanocluster structures are analyzed to highlight the system-specific differences across the three metals.

Highlights from Faraday Discussion on Nanoalloys: recent developments and future perspectives, London, UK.

In this article, we present a summary of the Faraday Discussion that took place on September 21-23, 2022 in London, UK. The primary goal of this event was to promote and discuss the recent developments in the field of nanoalloys. Here we briefly outline each scientific session as well as other conference events.

Machine Learning Assisted Clustering of Nanoparticle Structures.

We propose a scheme for the automatic separation (i.e., clustering) of data sets composed of several nanoparticle (NP) structures by means of Machine Learning techniques. These data sets originate from atomistic simulations, such as global optimizations searches and molecular dynamics simulations, which can produce large outputs that are often difficult to inspect by hand. By combining a description of NPs based on their local atomic environment with unsupervised learning algorithms, such as K-Means and Gaussian mixture model, we are able to distinguish between different structural motifs (e.g., icosahedra, decahedra, polyicosahedra, fcc fragments, twins, and so on). We show that this method is able to improve over the results obtained previously thanks to the successful implementation of a more detailed description of NPs, especially for systems showing a large variety of structures, including disordered ones.

Growth mechanisms from tetrahedral seeds to multiply twinned Au nanoparticles revealed by atomistic simulations.

The growth pathways from tetrahedral to multiply twinned gold nanoparticles in the gas phase are studied by molecular dynamics simulations supported by density functional theory calculations. Our results show that the growth from a tetrahedron to a multiple twin can take place by different pathways: directly from a tetrahedron to a decahedron (Th → Dh pathway), directly from a tetrahedron to an icosahedral fragment (Th → Ih), and from a tetrahedron to an icosahedron passing through an intermediate decahedron (Th → Dh → Ih). The simulations allow to determine the key atomic-level growth mechanism at the origin of twinning in metal nanoparticles. This mechanism is common to all these pathways and starts from the preferential nucleation of faulted atomic islands in the vicinity of facet edges, leading to the formation and stabilization of twin planes and of fivefold symmetry axes.

Regression and clustering algorithms for AgCu nanoalloys: from mixing energy predictions to structure recognition.

The lowest-energy structures of AgCu nanoalloys are searched for by global optimization algorithms for sizes 100 and 200 atoms depending on composition. Even though the AgCu system is very weakly miscible in macroscopic samples, the mixing energy for these nanoalloys turns out to be clearly negative for both sizes, a result which is attributed to the stabilization of non-crystalline Cu@Ag core-shell structures at the nanoscale. The mixing energy is a quantity nowadays unknown in its functional form, so that its prediction may take advantage of machine learning techniques. A support vector regressor is then implemented to successfully predict the mixing energy of AgCu nanoalloys of both sizes. Moreover, with the help of unsupervised learning algorithms, it is shown that the automatic classification of such nanoalloys into different physically meaningful structural families is indeed possible. Finally, thanks to the harmonic superposition approximation, the temperature-dependent probabilities of such structural families are calculated.

Shape Changes in AuPd Alloy Nanoparticles Controlled by Anisotropic Surface Stress Relaxation.

The shape of AuPd nanoparticles is engineered by surface stress relaxation, achieved by varying the Au content in nanoparticles of Pd-rich compositions. AuPd nanoparticles are grown in the gas phase for several compositions and growth conditions. Their structure is atomically resolved by HRTEM/STEM and EDX. In pure Pd distributions the dominant structures are FCC truncated octahedra (TO), while increasing the Au content there is a transition to icosahedral (Ih) structures in which Au atoms are preferentially placed at the nanoparticle surface. The transition is sharper for growth conditions closer to equilibrium. The physical origin of the transition is determined with the aid of computer simulations. Global optimization searches and free energy calculations confirm that Ih become the equilibrium structure for increasing the Au content. Atomic stress calculations demonstrate that the TO → Ih shape change is caused by a better relaxation of anisotropic surface stress in icosahedra.