Atomic-resolution imaging of surface and core melting in individual size-selected Au nanoclusters on carbon

Machine Learning Molecular Dynamics Shows Anomalous Entropic Effect on Catalysis through Surface Pre-melting of Nanoclusters

Due to the superior catalytic activity and efficient utilization of noble metals, nanocatalysts are extensively used in the modern industrial production of chemicals. The surface structures of these materials are significantly influenced by reactive adsorbates, leading to dynamic behavior under experimental conditions. The dynamic nature poses significant challenges in studying the structure-activity relations of catalysts. Herein, we unveil an anomalous entropic effect on catalysis via surface pre-melting of nanoclusters through machine learning accelerated molecular dynamics and free energy calculation. We find that due to the pre-melting of shell atoms, there exists a non-linear variation in the catalytic activity of the nanoclusters with temperature. Consequently, two notable changes in catalyst activity occur at the respective temperatures of melting for the shell and core atoms. We further study the nanoclusters with surface point defects, i.e. vacancy and ad-atom, and observe significant decrease in the surface melting temperatures of the nanoclusters, enabling the reaction to take place under more favorable and milder conditions. These findings not only provide novel insights into dynamic catalysis of nanoclusters but also offer new understanding of the role of point defects in catalytic processes.

Melting Is Well-Known, but Is It Also Well-Understood?

Contrary to continuous phase transitions, where renormalization group theory provides a general framework, for discontinuous phase transitions such a framework seems to be absent. Although the thermodynamics of the latter type of transitions is well-known and requires input from two phases, for melting a variety of one-phase theories and models based on solids has been proposed, as a generally accepted theory for liquids is (yet) missing. Each theory or model deals with a specific mechanism using typically one of the various defects (vacancies, interstitials, dislocations, interstitialcies) present in solids. Furthermore, recognizing that surfaces are often present, one distinguishes between mechanical or bulk melting and thermodynamic or surface-mediated melting. After providing the necessary preliminaries, we discuss both types of melting in relation to the various defects. Thereafter we deal with the effect of pressure on the melting process, followed by a discussion along the line of type of materials. Subsequently, some other aspects and approaches are dealt with. An attempt to put melting in perspective concludes this review.

Core atoms escape from the shell: reverse segregation of Pb-Al core-shell nanoclusters via nanoscale melting

Melting is a phase transition that profoundly affects the fabrication and diverse applications of metal nanoclusters. Core-shell clusters offer distinctive properties and thus opportunities compared with other classes of nano-alloys. Molecular dynamics simulations have been employed to investigate the melting behaviour of Pb-Al core-shell clusters containing a fixed Pb147 core and varying shell thickness. Our results show that the core and shell melt separately. Surprisingly, core melting always drives the core Pb atoms to break out the shell and coat the nanoclusters in a reversed segregation process at the nanoscale. The melting point of the core increases with the shell thickness to exceed that of the bare core cluster, but the thinnest shell always supresses the core melting point. These results can be a reference for the future fabrication, manipulation, and exploitation of the core-shell nanoalloys chosen. The system chosen is ideally suited for experimental observations.

Growth pathways of Cu shells on Au and AuCu seeds: interdiffusion, shape transformations, strained shells and patchy surfaces

The growth of AuCu nanoparticles obtained by depositing Cu atoms on starting seeds of pure Au and on mixed AuCu seeds is studied by molecular dynamics simulations. Depending on the shape of the seed, its composition and the growth temperature, different growth pathways are observed, in which several types of structural transformations take place. The final growth structures comprise Au@Cu core@shell arrangements as well as Janus-like structures with patchy surfaces. The results of the growth simulations are rationalized in terms of the activation of different diffusion processes, both on the surface and inside the growing clusters. These diffusion processes regulate structural transitions between different motifs and the occurrence of dewetting phenomena. The simulation results show that depositon of Cu atoms on pure Au or mixed AuCu seed can be an effective tool for producing clusters with uncommon surface atom arrangements of potential interest for catalysis.

Machine learning of atomic dynamics and statistical surface identities in gold nanoparticles

It is known that metal nanoparticles (NPs) may be dynamic and atoms may move within them even at fairly low temperatures. Characterizing such complex dynamics is key for understanding NPs' properties in realistic regimes, but detailed information on, e.g., the stability, survival, and interconversion rates of the atomic environments (AEs) populating them are non-trivial to attain. In this study, we decode the intricate atomic dynamics of metal NPs by using a machine learning approach analyzing high-dimensional data obtained from molecular dynamics simulations. Using different-shape gold NPs as a representative example, an AEs' dictionary allows us to label step-by-step the individual atoms in the NPs, identifying the native and non-native AEs and populating them along the MD simulations at various temperatures. By tracking the emergence, annihilation, lifetime, and dynamic interconversion of the AEs, our approach permits estimating a "statistical equivalent identity" for metal NPs, providing a comprehensive picture of the intrinsic atomic dynamics that shape their properties.

Atomic-scale observation of premelting at 2D lattice defects inside oxide crystals

Since two major criteria for melting were proposed by Lindemann and Born in the early 1900s, many simulations and observations have been carried out to elucidate the premelting phenomena largely at the crystal surfaces and grain boundaries below the bulk melting point. Although dislocations and clusters of vacancies and interstitials were predicted as possible origins to trigger the melting, experimental direct observations demonstrating the correlation of premelting with lattice defects inside a crystal remain elusive. Using atomic-column-resolved imaging with scanning transmission electron microscopy in polycrystalline BaCeO₃, here we clarify the initiation of melting at two-dimensional faults inside the crystals below the melting temperature. In particular, melting in a layer-by-layer manner rather than random nucleation at the early stage was identified as a notable finding. Emphasizing the value of direct atomistic observation, our study suggests that lattice defects inside crystals should not be overlooked as preferential nucleation sites for phase transformation including melting.

Fate of Gold Nanoparticles in Laser Desorption/Ionization Mass Spectrometry: Toward the Imaging of Individual Nanoparticles

This study focuses on mapping the spatial distribution of Au nanoparticles (NPs) by laser desorption/ionization mass spectrometry imaging (LDI MSI). Laser interaction with NPs and associated phenomena, such as change of shape, melting, migration, and release of Au ions, are explored at the single particle level. Arrays of dried droplets containing low numbers of spatially segregated NPs were reproducibly prepared by automated drop-on-demand piezo-dispensing and analyzed by LDI MSI using an ultrahigh resolution orbital trapping instrument. To enhance the signal from NPs, an in source gas-phase chemical reaction of generated Au ions with xylene was employed. The developed technique allowed the detecting, chemical characterization, and mapping of the spatial distribution of Au NPs; the ion signals were detected from as low as ten 50 nm Au NPs on a pixel. Furthermore, the Au NP melting dynamics under laser irradiation was monitored by correlative atomic force microscopy (AFM) and scanning electron microscopy (SEM). AFM measurements of Au NPs before and after LDI MSI analysis revealed changes in NP shape from a sphere to a half-ellipsoid and total volume reduction of NPs down to 45% of their initial volume.

Softness of hydrated salt crystals under deliquescence

Deliquescence is a first-order phase transition, happening when a salt absorbs water vapor. This has a major impact on the stability of crystalline powders that are important for example in pharmacology, food science and for our environment and climate. Here we show that during deliquescence, the abundant salt sodium sulfate decahydrate, mirabilite (Na₂SO₄·10H₂O), behaves differently than anhydrous salts. Using various microscopy techniques combined with Raman spectroscopy, we show that mirabilite crystals not only lose their facets but also become soft and deformable. As a result, microcrystals of mirabilite simultaneously behave crystalline-like in the core bulk and liquid-like at the surface. Defects at the surface can heal at a speed much faster than the deliquescence rate by the mechanism of visco-capillary flow over the surface. While magnesium sulfate hexahydrate (MgSO₄⋅6H₂O) behaves similarly during deliquescence, a soft and deformable state is completely absent for the anhydrous salts sodium chloride (NaCl) and sodium sulfate thenardite (Na₂SO₄). The results highlight the effect of crystalline water, and its mobility in the crystalline structure on the observed softness during deliquescence. Controlled hydrated salts have potential applications such as thermal energy storage, where the key parameter is relative humidity rather than temperature.

On the melting point depression, coalescence, and chemical ordering of bimetallic nanoparticles: the miscible Ni-Pt system

Among the properties that distinguish nanoparticles (NPs) from their bulk counterparts is their lower melting points. It is also common knowledge that relatively low melting points enhance the coalescence of (usually) nascent nanoclusters toward larger NPs. Finally, it is well established that the chemical ordering of bi- (or multi-) metallic NPs can have a profound effect on their physical and chemical properties, dictating their potential applications. With these three considerations in mind, we investigated the coalescence mechanisms for Ni and Pt NPs of various configurations using classical molecular dynamics (MD) computer simulations. Benchmarking the coalescence process, we identified a steeper melting point depression for Pt than for Ni, which indicates a reversal in the order of melting for same-size NPs of the two elements. This reversal, also evident in the nano-phase diagram thermodynamically constructed using the regular solution model, may be useful for utilising NP coalescence as a means to design and engineer non-equilibrium NPs via gas-phase synthesis. Indeed, our MD simulations revealed different coalescence mechanisms at play depending on the conditions, leading to segregated chemical orderings such as quasi-Janus core-satellite, or core-(partial) shell NPs, despite the expected theoretical tendency for elemental mixing.

When mechanisms of coalescence and sintering at the nanoscale fundamentally differ: Molecular dynamics study

Employing classical isothermal molecular dynamics, we simulated coalescence of mesoscopic Au nanodroplets, containing from several thousands to several hundred thousands of atoms, and sintering of mesoscopic solid Au nanoparticles. For our atomistic simulations, we used the embedded atom method. The employed open access program large-scale atomic/molecular massively parallel simulator makes it possible to realize parallel graphical processing unit calculations. We have made a conclusion that the regularities and mechanisms of the nanodroplet coalescence (temperature is higher than the nanoparticle melting temperature) and of the solid nanoparticle sintering differ from each other. We have also concluded that the nanodroplet coalescence may be interpreted as a hydrodynamic phenomenon at the nanoscale whereas sintering of solid nanoparticles is a much more complex phenomenon related to different mechanisms, including collective rearrangements of atoms, the surface diffusion, and other types of diffusion. At the same time, collective rearrangements of atoms relate not only to the solid nanoparticle sintering but also to the nanodroplet coalescence. In general, our molecular dynamics results on sintering of Au nanoparticles consisting of 10 000–30 000 atoms agree with the Ferrando–Minnai kinetic trapping concept that was earlier confirmed in molecular dynamics experiments on Au nanoclusters consisting of about 100 atoms.

Melting at Mg/Al interface in Mg-Al-Mg nanolayer by molecular dynamics simulations

The melting at the magnesium/aluminum (Mg/Al) interface is an essential step during the fabrications of Mg-Al structural materials and biomaterials. We carried out molecular dynamics simulations on the melting at the Mg/Al interface in a Mg-Al-Mg nanolayer via analyzing the changes of average atomic potential energy, Lindemann index, heat capacity, atomic density distribution and radial distribution function with temperature. The melting temperatures (Tm) of the nanolayer and the slabs near the interface are significantly sensitive to the heating rate (vh) over the range ofvh ≤ 4.0 K ps^-1. The distance (d) range in which the interface affects the melting of the slabs is predicted to be (-98.2, 89.9) Å atvh→0,if the interface is put atd = 0 and Mg (Al) is located at the left (right) side of the interface. TheTmof the Mg (Al) slab just near the interface (e.g.d=4.0Å) is predicted to be 926.8 K (926.6 K) atvh→0,with 36.9 K (37.1 K) below 963.7 K for the nanolayer. These results highlight the importance of regional research on the melting at an interface in the nanolayers consisting of two different metals.

Realistic Modelling of Dynamics at Nanostructured Interfaces Relevant to Heterogeneous Catalysis

The focus of this short review is directed towards investigations of the dynamics of nanostructured metallic heterogeneous catalysts and the evolution of interfaces during reaction—namely, the metal–gas, metal–liquid, and metal–support interfaces. Indeed, it is of considerable interest to know how a metal catalyst surface responds to gas or liquid adsorption under reaction conditions, and how its structure and catalytic properties evolve as a function of its interaction with the support. This short review aims to offer the reader a birds-eye view of state-of-the-art methods that enable more realistic simulation of dynamical phenomena at nanostructured interfaces by exploiting resource-efficient methods and/or the development of computational hardware and software.

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...

Encapsulation of gold nanoclusters: stabilization and more

Gold nanoparticles with only a few atoms, known as gold nanoclusters (AuNCs), have dimensions below 2 nm and feature singular properties such as size dependent luminescence. AuNCs are also highly photostable and have catalytic activity, low toxicity and good biocompatibility. With these properties, they are extremely promising candidates for application in bioimaging, sensing and catalysis. However, when stabilized only with small capping ligands, their use is hindered by lack of colloidal stability. Encapsulation of the AuNCs can contribute to provide a more robust protection and even to improve their properties. Here, we review the encapsulation of AuNCs in polymers, silica and metal organic frameworks (MOFs) for applications in bioimaging, sensing and catalysis.

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.

Interior Melting of Rapidly Heated Gold Nanoparticles

Normal melting invariably starts from surfaces or interfaces due to the weaker bonding constraints in these regions. However, we show that melting can be initiated from the interior of gold nanoparticles with high heating rates. We find that melting starts from the surface with the formation of a premelting layer, as usual, but that the premelting layer does not extend to the interior under certain conditions. Instead, liquid nucleation occurs in the core of the nanoparticle. This unexpected interior melting is connected to the slower melting kinetics, which is related to heat transfer near the premelted surface. The required conditions for interior melting are a suitable size of the nanoparticle and a sufficiently fast heating rate. The present results point to a novel melting regime in nanoparticles. We note that the time scales are now accessible using ultrafast tools such as X-ray lasers that can probe dynamical structure changes, suggesting opportunities for experiments.

Physico-chemical properties of selenium-tellurium alloys across the scales

Selenium and tellurium are both energy critical elements as defined by the American Physical Society and the Materials Research Society. When mixed together, both elements form an alloy. The size- and shape-dependent thermal and optical properties of this alloy are investigated in this manuscript by using nano-thermodynamics and machine learning techniques. This alloy is found to have particularly interesting properties for solar cell applications.

Sintering Bonding of SiC Particulate Reinforced Aluminum Metal Matrix Composites by Using Cu Nanoparticles and Liquid Ga in Air

SiC particulate reinforced aluminum metal matrix composites (SiC_p/Al MMCs) are characterized by controllable thermal expansion, high thermal conductivity and lightness. These properties, in fact, define the new promotional material in areas and industries such as the aerospace, automotive and electrocommunication industries. However, the poor weldability of this material becomes its key problem for large-scale applications. Sintering bonding technology was developed to join SiC_p/Al MMCs. Cu nanoparticles and liquid Ga were employed as self-fluxing filler metal in air under joining temperatures ranging from 400 °C to 500 °C, with soaking time of 2 h and pressure of 3 MPa. The mechanical properties, microstructure and gas tightness of the joint were investigated. The microstructure analysis demonstrated that the joint was achieved by metallurgical bonding at contact interface, and the sintered layer was composed of polycrystals. The distribution of Ga was quite homogenous in both of sintered layer and joint area. The maximum level of joint shear strength of 56.2 MPa has been obtained at bonding temperature of 450 °C. The specimens sintering bonded in temperature range of 440 °C to 460 °C had qualified gas tightness during the service, which can remain 10^-10 Pa·m³/s.

Melting Behavior of Bimetallic and Trimetallic Nanoparticles: A Review of MD Simulation Studies

In recent years, bimetallic and trimetallic nanoparticles (NPs) have become attractive materials for many researchers especially in the field of catalysis due to their interesting physical and chemical properties. These unique properties arise mainly from simultaneous effects of two different metal atoms in their structure. In this review, recent theoretical studies on these NPs using molecular dynamics simulation are presented. Since investigation of thermodynamic stabilities of metallic NPs is a critical factor in their construction for catalytic applications, our focus in this review is on the thermal stability of bimetallic and trimetallic NPs. The melting behavior of these materials with different atomic arrangements including core-shell, three-shell, crown-jewel, ordered and disordered alloy, and Janus materials are discussed. Other factors including stress, strain, atomic radius, thermal expansion coefficient, cohesive energy, surface energy, size, composition, and morphology are described in detail, because these properties lead to complexity in the melting behavior of bimetallic and trimetallic NPs.

Development of a Structural Comparison Method to Promote Exploration of the Potential Energy Surface in the Global Optimization of Nanoclusters

A structural comparison method (SCM) was created to quantify the structural diversity of nanoclusters and was implemented into a global optimization algorithm to evaluate structural diversity between generated clusters on the fly and promote exploration of the potential energy surface. The SCM evaluated topological differences between clusters using the common neighbor analysis and provided a numerical measure of similarity between the two clusters. The SCM was implemented into a genetic algorithm by integrating it into a new structure + energy fitness operator such that structural diversity of clusters in the population and their energies were used to assign fitness values to clusters. The efficiency of the genetic algorithm with this new fitness operator was benchmarked against several Lennard-Jones clusters (LJ₃₈, LJ₇₅, and LJ₉₈) known to be difficult cases for global optimization algorithms. For LJ₃₈ and LJ₇₅, this new structure + energy fitness operator performed equally well or better than the energy fitness operator. However, the efficiency of locating the global minimum of LJ₉₈ decreased using this new structure + energy fitness operator. Further analysis of the genetic algorithm with this fitness operator showed that the algorithm did indeed promote exploration of the PES of LJ₉₈ as desired but hindered refinement of clusters, preventing it from locating the global minimum even if the energy funnel of the global minimum had been located.

The pure and representative types of disordered platinum nanoparticles from machine learning

The development of interpretable structure/property relationships is a cornerstone of nanoscience, but can be challenging when the structural diversity and complexity exceeds our ability to characterise it. This is often the case for imperfect, disordered and amorphous nanoparticles, where even the nomenclature can be unspecific. Disordered platinum nanoparticles have exhibited superior performance for some reactions, which makes a systematic way of describing them highly desirable. In this study we have used a diverse set of disorder platinum nanoparticles and machine learning to identify the pure and representative structures based on their similarity in 121 dimensions. We identify two prototypes that are representative of separable classes, and seven archetypes that are the pure structures on the convex hull with which all other possibilities can be described. Together these nine nanoparticles can explain all of the variance in the set, and can be described as either single crystal, twinned, spherical or branched; with or without roughened surfaces. This forms a robust sub-set of platinum nanoparticle upon which to base further work, and provides a theoretical basis for discussing structure/property relationships of platinum nanoparticles that are not geometrically ideal.

Rapid and sensitive detection of melanin using glutathione conjugated gold nanocluster based fluorescence quenching assay

In the present study, a rapid, facile, and highly sensitive assay based on glutathione conjugated gold nanocluster (GSH-AuNCs) is developed for the detection of melanin. The analysis of melanin which is linked to several diseases is crucial. The current methods for melanin estimation are complex and long, thus demands an alternative technology. In general, melanin exhibits photoactive properties, thus, it might have fluorescence quenching properties through the phenomenon of fluorescence resonance energy transfer. To verify our assumption, we have developed the fluorescence quenching assay based on gold nanocluster and melanin interaction. As a result, under the optimized condition, the developed quenching assay demonstrated the high selectivity and sensitivity toward melanin with a limit of detection and correlation coefficient of 0.060 μg/mL and 0.993, respectively. Moreover, the whole process represented the rapid assay time of 30 min to complete. To validate the performance of our assay on real samples, B16F1 cells lysate, and hair samples were tested that provided satisfactory results. Therefore, we believe that our assay due to good sensitivity and short assay time could be beneficial for the clinical diagnosis of melanin in the future study.

An Element-Based Generalized Coordination Number for Predicting the Oxygen Binding Energy on Pt3M (M = Co, Ni, or Cu) Alloy Nanoparticles

We studied the binding energies of O species on face-centered-cubic Pt3M nanoparticles (NPs) with a Pt-skin layer using density functional theory calculations, where M is Co, Ni, or Cu. It is desirable to express the property by structural parameters rather than by calculated electronic structures such as the d-band center. A generalized coordination number (GCN) is an effective descriptor to predict atomic or molecular adsorption energy on Pt-NPs. The GCN was extended to the prediction of highly active sites for oxygen reduction reaction. However, it failed to explain the O binding energies on Pt-skin Pt150M51-NPs. In this study, we introduced an element-based GCN, denoted as GCNA-B, and considered it as a descriptor for supervised learning. The obtained regression coefficients of GCNPt-Pt were smaller than those of the other GCNA-B. With increasing M atoms in the subsurface layer, GCNPt-M, GCNM-Pt, and GCNM-M increased. These factors could reproduce the calculated result that the O binding energies of the Pt-skin Pt150M51-NPs were less negative than those of the Pt201-NPs. Thus, GCNA-B explains the ligand effect of the O binding energy on the Pt-skin Pt150M51-NPs.

Three-dimensional atomic structure of supported Au nanoparticles at high temperature

Au nanoparticles (NPs) deposited on CeO2 are extensively used as thermal catalysts since the morphology of the NPs is expected to be stable at elevated temperatures. Although it is well known that the activity of Au NPs depends on their size and surface structure, their three-dimensional (3D) structure at the atomic scale has not been completely characterized as a function of temperature. In this paper, we overcome the limitations of conventional electron tomography by combining atom counting applied to aberration-corrected scanning transmission electron microscopy images and molecular dynamics relaxation. In this manner, we are able to perform an atomic resolution 3D investigation of supported Au NPs. Our results enable us to characterize the 3D equilibrium structure of single NPs as a function of temperature. Moreover, the dynamic 3D structural evolution of the NPs at high temperatures, including surface layer jumping and crystalline transformations, has been studied.

Atomic-Resolution Imaging of Fast Nanoscale Dynamics with Bright Microsecond Electron Pulses

Atomic-resolution electron microscopy is a crucial tool to elucidate the structure of matter. Recently, fast electron cameras have added the time domain to high-resolution imaging, allowing static images to be acquired as movies from which sample drift can later be removed computationally and enabling real-time observations of atomic-scale dynamics on the millisecond time scale. Even higher time resolution can be achieved with short electron pulses, yet their potential for atomic-resolution imaging remains unexplored. Here, we generate high-brightness microsecond electron pulses from a Schottky emitter whose current we briefly drive to near its limit. We demonstrate that drift-corrected imaging with such pulses can achieve atomic resolution in the presence of much larger amounts of drift than with a continuous electron beam. Moreover, such pulses enable atomic-resolution observations on the microsecond time scale, which we employ to elucidate the crystallization pathways of individual metal nanoparticles as well as the high-temperature transformation of perovskite nanocrystals.

Beam generation and structural optimization of size-selected Au923 clusters

A size-selected beam of Au_923±20 clusters is generated in a gas-phase condensation cluster source equipped with a lateral time-of-flight mass selector. The beam current reaches up to 9.13 nA for small clusters and 80 pA for Au_923±20 clusters, which are then analyzed using a scanning transmission electron microscope. Four types of metastable structures are observed for the Au_923±20 clusters, including ino-decahedron (Dh), cuboctahedron and icosahedron (Ih). The proportion of bulk-favorable cuboctahedron (i.e. face center cubic (Fcc)) structure takes up only 10-20%, while the penta-rotating symmetrical structures (Dh/Ih) are the dominant ones which take up over three quarters. Changing the beam condition may optimize the clusters from Dh-dominant to the Ih-dominant phase, which paves the way towards nanoparticle control beyond the diameters.

Structure and orientation effects in the coalescence of Au clusters

The atomic configuration of nanoparticles is key to their properties, in a way that resembles the structure-function correlation of biomolecules, and depends on the growth mechanism. Coalescence is often an important step in the growth of nanoparticles, both in liquid and in the gas phase. In coalescence, two preformed clusters collide and merge to form a larger aggregate, whose shape evolves from an initial configuration, which is strongly out of equilibrium, towards more compact structures. Here the coalescence in the gas phase of gold clusters of size ∼2 nm is simulated by the Molecular Dynamics (MD) method. Our simulations reveal a persistent influence of the structure and relative orientation of the initial colliding clusters on the final coalesced aggregates, even after more than 1 μs at temperature T = 500 K. This result is interpreted in terms of a special type of kinetic trapping, in which the choice of the structural motif takes place in the initial stages of the coalescence process. In the subsequent evolution, the coalescing aggregate may equilibrate within that motif, while transformations between different motifs are not observed, so that inter-motif equilibration is not achieved. Inter-motif equilibration is only achieved at 550 K and above. The simulations also show that aggregate reshaping occurs by a variety of specific transformation pathways, which often involve the concerted displacements of many atoms.

Fluorochromic polymer films containing ultrasmall silver nanoclusters

Fluorochromic materials that change their emission properties in response to their environment are of interest for the development of sensors, optical data storage and light-emitting materials. A thermally fluorochromic elastic polymer film that exhibits remarkable fluorochromism (from red to yellow) and enhancement of fluorescence intensity after thermal treatment (>120 °C) is designed by the incorporation of silver nanoclusters. The thermal treatment also leads to a significant increase of quantum yield and fluorescence lifetime. It is found that the thermo-induced etching on larger silver nanoclusters generates smaller silver nanoclusters. This simple and efficient size-tuning process in solid state is responsible for the thermo-fluorochromism and enhancement of fluorescence emission from silver nanoclusters. Such a thermo-fluorochromic polymer material is finally demonstrated to be useful for thermo-printing. This material illustrates a new way to make smart optical materials, particularly for potential applications in optical data storage and soft OLED display.