Structure, thermodynamics, and rearrangement mechanisms in gold clusters-insights from the energy landscapes framework.

We consider finite-size and temperature effects on the structure of model AuN clusters (30 ≤ N ≤ 147) bound by the Gupta potential. Equilibrium behaviour is examined in the harmonic superposition approximation, and the size-dependent melting temperature is also bracketed using molecular dynamics simulations. We identify structural transitions between distinctly different morphologies, characterised by various defect features. Reentrant behaviour and trends with respect to cluster size and temperature are discussed in detail. For N = 55, 85, and 147 we visualise the topography of the underlying potential energy landscape using disconnectivity graphs, colour-coded by the cluster morphology; and we use discrete path sampling to characterise the rearrangement mechanisms between competing structures separated by high energy barriers (up to 1 eV). The fastest transition pathways generally involve metastable states with multiple fivefold disclinations and/or a high degree of amorphisation, indicative of melting. For N = 55 we find that reoptimising low-lying minima using density functional theory (DFT) alters their energetic ordering and produces a new putative global minimum at the DFT level; however, the equilibrium structure predicted by the Gupta potential at room temperature is consistent with previous experiments

Thermodynamics of CuPt nanoalloys.

The control of structural and chemical transitions in bimetallic nanoalloys at finite temperatures is one of the challenges for their use in advanced applications. Comparing Nested Sampling and Molecular Dynamics simulations, we investigate the phase changes of CuPt nanoalloys with the aim to elucidate the role of kinetic effects during their solidification and melting processes. We find that the quasi-thermodynamic limit for the nucleation of (CuPt)309 is 965 ± 10 K, but its prediction is increasingly underestimated when the system is cooled faster than 109 K/s. The solidified nanoparticles, classified following a novel tool based on Steinhardt parameters and the relative orientation of characteristic atomic environments, are then heated back to their liquid phase. We demonstrate the kinetic origin of the hysteresis in the caloric curve as (i) it closes for rates slower than 108 K/s, with a phase change temperature of 970 K ± 25 K, in very good agreement with its quasi-thermodynamic limit; (ii) the process happens simultaneously in the inner and outer layers; (iii) an onion-shell chemical order - Cu-rich surface, Pt-rich sub-surface, and mixed core - is always preserved

A diffusion Monte Carlo study of small para-Hydrogen clusters

Ground state energies and chemical potentials of parahydrogen clusters are calculated from 3 to 40 molecules using the diffusion Monte Carlo technique with two different pH2-pH2 interactions. This calculation improves a previous one by the inclusion of three-body correlations in the importance sampling, by the time step adjustement and by a better estimation of the statistical errors. Apart from the cluster with 13 molecules, no other magic clusters are predicted, in contrast with path integral Monte Carlo results

Data-driven simulation and characterisation of gold nanoparticle melting

The simulation and analysis of the thermal stability of nanoparticles, a stepping stone towards their application in technological devices, require fast and accurate force fields, in conjunction with effective characterisation methods. In this work, we develop efficient, transferable, and interpretable machine learning force fields for gold nanoparticles based on data gathered from Density Functional Theory calculations. We use them to investigate the thermodynamic stability of gold nanoparticles of different sizes (1 to 6 nm), containing up to 6266 atoms, concerning a solid-liquid phase change through molecular dynamics simulations. We predict nanoparticle melting temperatures in good agreement with available experimental data. Furthermore, we characterize the solid-liquid phase change mechanism employing an unsupervised learning scheme to categorize local atomic environments. We thus provide a data-driven definition of liquid atomic arrangements in the inner and surface regions of a nanoparticle and employ it to show that melting initiates at the outer layers

Close-Packing of Clusters: Application to Al_100

The lowest energy configurations of close-packed clusters up to N=110 atoms with stacking faults are studied using the Monte Carlo method with Metropolis algorithm. Two types of contact interactions, a pair-potential and a many-atom interaction, are used. Enhanced stability is shown for N=12, 26, 38, 50, 59, 61, 68, 75, 79, 86, 100 and 102, of which only the sizes 38, 75, 79, 86, and 102 are pure FCC clusters, the others having stacking faults. A connection between the model potential and density functional calculations is studied in the case of Al_100. The density functional calculations are consistent with the experimental fact that there exist epitaxially grown FCC clusters starting from relatively small cluster sizes. Calculations also show that several other close-packed motifs existwith comparable total energies.Comment: 9 pages, 7 figure

Molecular dynamics simulations of lead clusters

Molecular dynamics simulations of nanometer-sized lead clusters have been performed using the Lim, Ong and Ercolessi glue potential (Surf. Sci. {\bf 269/270}, 1109 (1992)). The binding energies of clusters forming crystalline (fcc), decahedron and icosahedron structures are compared, showing that fcc cuboctahedra are the most energetically favoured of these polyhedral model structures. However, simulations of the freezing of liquid droplets produced a characteristic form of ``shaved'' icosahedron, in which atoms are absent at the edges and apexes of the polyhedron. This arrangement is energetically favoured for 600-4000 atom clusters. Larger clusters favour crystalline structures. Indeed, simulated freezing of a 6525-atom liquid droplet produced an imperfect fcc Wulff particle, containing a number of parallel stacking faults. The effects of temperature on the preferred structure of crystalline clusters below the melting point have been considered. The implications of these results for the interpretation of experimental data is discussed.Comment: 11 pages, 18 figues, new section added and one figure added, other minor changes for publicatio

Experimental determination of the energy difference between competing isomers of deposited, size-selected gold nanoclusters

The equilibrium structures and dynamics of a nanoscale system are regulated by a complex potential energy surface (PES). This is a key target of theoretical calculations but experimentally elusive. We report the measurement of a key PES parameter for a model nanosystem: size-selected Au nanoclusters, soft-landed on amorphous silicon nitride supports. We obtain the energy difference between the most abundant structural isomers of magic number Au561 clusters, the decahedron and face-centred-cubic (fcc) structures, from the equilibrium proportions of the isomers. These are measured by atomic-resolution scanning transmission electron microscopy, with an ultra-stable heating stage, as a function of temperature (125–500 °C). At lower temperatures (20–125 °C) the behaviour is kinetic, exhibiting down conversion of metastable decahedra into fcc structures; the higher state is repopulated at higher temperatures in equilibrium. We find the decahedron is 0.040 ± 0.020 eV higher in energy than the fcc isomer, providing a benchmark for the theoretical treatment of nanoparticles

Coalescence of nanoscale metal clusters: Molecular-dynamics study

We study the coalescence of nanoscale metal clusters in an inert-gas atmosphere using constant-energy molecular dynamics. The coalescence proceeds via atomic diffusion with the release of surface energy raising the temperature. If the temperature exceeds the melting point of the coalesced cluster, a molten droplet forms. If the temperature falls between the melting point of the larger cluster and those of the smaller clusters, a metastable molten droplet forms and freezes.Comment: 5 figure