In recent years, due to its inherent flexibility, magnetron-sputtering has been widely used to synthesise bi-metallic nanoparticles (NPs) via subsequent inert-gas cooling and gas-phase condensation of the sputtered atomic vapour. Utilising two separate sputter targets allows for good control over composition. Simultaneously, it involves fast kinetics and non-equilibrium processes, which can trap the nascent NPs into metastable configurations. In this study, we observed such configurations in immiscible, bi-metallic Ag–Cu NPs by scanning transmission electron microscopy (S/TEM) and electron energy-loss spectroscopy (EELS), and noticed a marked difference in the shape of NPs belonging to Ag- and Cu-rich samples. We explained the formation of Janus or Ag@Cu core/shell metastable structures on the grounds of in-flight mixed NP coalescence. We utilised molecular dynamics (MD) and Monte Carlo (MC) computer simulations to demonstrate that such configurations cannot occur as a result of nanoalloy segregation. Instead, sintering at relatively low temperatures can give rise to metastable structures, which eventually can be stabilised by subsequent quenching. Furthermore, we compared the heteroepitaxial diffusivities along various surfaces of both Ag and Cu NPs, and emphasised the differences between the sintering mechanisms of Ag- and Cu-rich NP compositions: small Cu NPs deform as coherent objects on large Ag NPs, whereas small Ag NPs dissolve into large Cu NPs, with their atoms diffusing along specific directions. Taking advantage of this observation, we propose controlled NP coalescence as a method to engineer mixed NPs of a unique, patterned core@partial-shell structure, which we refer to as a “glass-float” (ukidama) structure.

The coalescence of nanoclusters fabricated in the gas phase is a fundamental growth mechanism determining cluster shapes, sizes, compositions, and structures, with resultant effects on practically all of their physical and chemical properties. Furthermore, coalescence can affect properties of larger structures that consist of nanoparticles as their elementary building blocks, such as the fractal dimension of cluster aggregates and the porosity and conductance of thin films. Therefore, it comes as no surprise that a great body of research, both experimental and theoretical, has focused on nanoparticle coalescence over the course of the past few decades. This review attempts to summarize the most important recent results from computational studies on nanoparticle coalescence and draw parallels between theoretical and experimental findings. The approach used here aspires to explain nanoparticle coalescence within the framework of a single intuitive narrative by integrating previous results obtained using various methods by the authors and others. Simultaneously, it is discussed where understanding and controlling (i.e., enhancing or inhibiting) nanoparticle coalescence can have great technological interest.

Although the changes in melting behaviour on the nanoscale have long attracted the interest of researchers, the mechanism by which nanoparticles melt remains an open problem. We report the direct observation, at atomic resolution, of surface melting in individual size-selected Au clusters (2–5 nm diameter) supported on carbon films, using an in situ heating stage in the aberration corrected scanning transmission electron microscope. At elevated temperatures the Au nanoparticles are found to form a solid core-liquid shell structure. The cluster surface melting temperatures, show evidence of size-dependent melting point suppression. The cluster core melting temperatures are significantly greater than predicted by existing models of free clusters. To explore the effect of the interaction between the clusters and the carbon substrate, we employ a very large-scale ab initio simulation approach to investigate the influence of the support. Theoretical results for surface and core melting points are in good agreement with experiment.

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.

InAlN thin films grown on $\text{GaN}/{\text{Al}}_2{\text{O}}_3$ (0001) templates by metal-organic vapor phase epitaxy were studied by transmission electron microscopy techniques. V-defects in the form of hexagonal inverted pyramids with $\left\{10\overline{1}1\right\}$ sidewalls were observed on the films’ surfaces linked to the termination of threading dislocations. Their origin is explained by the different surface atom mobility of In and Al and the built-in strain relaxation. Indium segregation in the films is influenced by the formation of V-defects, the edges and the apexes of which function as paths of migrating indium atoms diffusing along nanopipes formed at the open-core threading dislocations.