Spontaneous alloying in binary metal microclusters - A molecular dynamics study -

Microcanonical molecular dynamics study of the spontaneous alloying(SA), which is a manifestation of fast atomic diffusion in a nano-sized metal cluster, is done in terms of a simple two dimensional binary Morse model. Important features observed by Yasuda and Mori are well reproduced in our simulation. The temperature dependence and size dependence of the SA phenomena are extensively explored by examining long time dynamics. The dominant role of negative heat of solution in completing the SA is also discussed. We point out that a presence of melting surface induces the diffusion of core atoms even if they are solid-like. In other words, the {\it surface melting} at substantially low temperature plays a key role in attaining the SA.Comment: 15 pages, 12 fgures, Submitted to Phys.Rev.

Melting Point and Lattice Parameter Shifts in Supported Metal Nanoclusters

The dependencies of the melting point and the lattice parameter of supported metal nanoclusters as functions of clusters height are theoretically investigated in the framework of the uniform approach. The vacancy mechanism describing the melting point and the lattice parameter shifts in nanoclusters with decrease of their size is proposed. It is shown that under the high vacuum conditions (p<10^-7 torr) the essential role in clusters melting point and lattice parameter shifts is played by the van der Waals forces of cluster-substrate interation. The proposed model satisfactorily accounts for the experimental data.Comment: 6 pages, 3 figures, 1 tabl

Superconductivity in the YIr2Si2 and LaIr2Si2 Polymorphs

We report on existence of superconductivity in YIr2Si2 and LaIr2Si2 compounds in relation to crystal structure. The two compounds crystallize in two structural polymorphs, both tetragonal. The high temperature polymorph (HTP) adopts the CaBe2Ge2-structure type (space group P4/nmm) while the low temperature polymorph (LTP) is of the ThCr2Si2 type (I4/mmm). By studying polycrystals prepared by arc melting we have observed that the rapidly cooled samples retain the HTP even at room temperature (RT) and below. Annealing such samples at 900C followed by slow cooling to RT provides the LTP. Both, the HTP and LTP were subsequently studied with respect to magnetism and superconductivity by electrical resistivity, magnetization, AC susceptibility and specific heat measurements. The HTP and LTP of both compounds respectively, behave as Pauli paramagnets. Superconductivity has been found exclusively in the HTP of both compounds below Tsc (= 2.52 K in YIr2Si2 and 1.24 K in LaIr2Si2). The relations of magnetism and superconductivity with the electronic and crystal structure are discussed with comparing experimental data with the results of first principles electronic structure calculations

Thermodynamics of Na_8 and Na_{20} clusters studied with ab-initio electronic structure methods

We study the thermodynamics of Na_8 and Na_{20} clusters using multiple-histogram methods and an ab initio treatment of the valence electrons within density functional theory. We consider the influence of various electron kinetic-energy functionals and pseudopotentials on the canonical ionic specific heats. The results for all models we consider show qualitative similarities, but also significant temperature shifts from model to model of peaks and other features in the specific-heat curves. The use of phenomenological pseudopotentials shifts the melting peak substantially (~ 50--100 K) when compared to ab-initio results. It is argued that the choice of a good pseudopotential and use of better electronic kinetic-energy functionals has the potential for performing large time scale and large sized thermodynamical simulations on clusters.Comment: LaTeX file and EPS figures. 24 pages, 13 figures. Submitted to Phys. Rev.

Diffusion of gold nanoclusters on graphite

We present a detailed molecular-dynamics study of the diffusion and coalescence of large (249-atom) gold clusters on graphite surfaces. The diffusivity of monoclusters is found to be comparable to that for single adatoms. Likewise, and even more important, cluster dimers are also found to diffuse at a rate which is comparable to that for adatoms and monoclusters. As a consequence, large islands formed by cluster aggregation are also expected to be mobile. Using kinetic Monte Carlo simulations, and assuming a proper scaling law for the dependence on size of the diffusivity of large clusters, we find that islands consisting of as many as 100 monoclusters should exhibit significant mobility. This result has profound implications for the morphology of cluster-assembled materials

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

Thermodynamics of tin clusters

We report the results of detailed thermodynamic investigations of the Sn$_{20}$ cluster using density-functional molecular dynamics. These simulations have been performed over a temperature range of 150 to 3000 K, with a total simulation time of order 1 ns. The prolate ground state and low-lying isomers consist of two tricapped trigonal prism (TTP) units stacked end to end. The ionic specific heat, calculated via a multihistogram fit, shows a small peak around 500 K and a shoulder around 850 K. The main peak occurs around 1200 K, about 700 K higher than the bulk melting temperature, but significantly lower than that for Sn$_{10}$. The main peak is accompanied by a sharp change in the prolate shape of the cluster due to the fusion of the two TTP units to form a compact, near spherical structure with a diffusive liquidlike ionic motion. The small peak at 500 K is associated with rearrangement processes within the TTP units, while the shoulder at 850 K corresponds to distortion of at least one TTP unit, preserving the overall prolate shape of the cluster. At all temperatures observed, the bonding remains covalent.Comment: Latex File and EPS Figures. 18 pages,11 Figures. Submitted to Phys. Rev.

Personalisation in MOOCs: a critical literature review

The advent and rise of Massive Open Online Courses (MOOCs) have brought many issues to the area of educational technology. Researchers in the field have been addressing these issues such as pedagogical quality of MOOCs, high attrition rates, and sustainability of MOOCs. However, MOOCs personalisation has not been subject of the wide discussions around MOOCs. This paper presents a critical literature survey and analysis of the available literature on personalisation in MOOCs to identify the needs, the current states and efforts to personalise learning in MOOCs. The findings illustrate that there is a growing attention to personalisation to improve learners’ individual learning experiences in MOOCs. In order to implement personalised services, personalised learning path, personalised assessment and feedback, personalised forum thread and recommendation service for related learning materials or learning tasks are commonly applied

Machine learning for beam dynamics studies at the CERN Large Hadron Collider

Machine learning entails a broad range of techniques that have been widely used in Science and Engineering since decades. High-energy physics has also profited from the power of these tools for advanced analysis of colliders data. It is only up until recently that Machine Learning has started to be applied successfully in the domain of Accelerator Physics, which is testified by intense efforts deployed in this domain by several laboratories worldwide. This is also the case of CERN, where recently focused efforts have been devoted to the application of Machine Learning techniques to beam dynamics studies at the Large Hadron Collider (LHC). This implies a wide spectrum of applications from beam measurements and machine performance optimisation to analysis of numerical data from tracking simulations of non-linear beam dynamics. In this paper, the LHC-related applications that are currently pursued are presented and discussed in detail, paying also attention to future developments

The Intensity of IUGR-Induced Transcriptome Deregulations Is Inversely Correlated with the Onset of Organ Function in a Rat Model

A low-protein diet applied during pregnancy in the rat results in intrauterine growth restricted (IUGR) fetuses. In humans, IUGR is associated with increased perinatal morbidity, higher incidence of neuro-developmental defects and increased risk of adult metabolic anomalies, such as diabetes and cardiovascular disease. Development and function of many organs are affected by environmental conditions such as those inducing fetal and early postnatal growth restriction. This phenomenon, termed “fetal programming” has been studied unconnectedly in some organs, but very few studies (if any) have investigated at the same time several organs, on a more comparative basis. However, it is quite probable that IUGR affects differentially most organ systems, with possible persistent changes in gene expression. In this study we address transcriptional alterations induced by IUGR in a multi-organ perspective, by systematic analysis of 20-days rat fetuses. We show that (1) expressional alterations are apparently stronger in organs functioning late in foetal or postnatal life than in organs that are functioning early (2) hierarchical classification of the deregulations put together kidney and placenta in one cluster, liver, lungs and heart in another; (3) the epigenetic machinery is set up especially in the placenta, while its alterations are rather mild in other organs; (4) the genes appear deregulated in chromosome clusters; (5) the altered expression cascades varies from organ to organ, with noticeably a very significant modification of the complement and coagulation cascades in the kidney; (6) we found a significant increase in TF binding site for HNF4 proteins specifically for liver genes that are down-regulated in IUGR, suggesting that this decrease is achieved through the action of HNF transcription factors, that are themselves transcriptionnally induced in the liver by IUGR (x 1.84 fold). Altogether, our study suggests that a combination of tissue-specific mechanisms contributes to bring about tissue-driven modifications of gene cascades. The question of these cascades being activated to adapt the organ to harsh environmental condition, or as an endpoint consequence is still raised