Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

Mechanical alloying (MA) is a solid-state powder processng technique involving repeated welding, fracturing, and rewelding of powder particles in a high-energy ball mill. Originally developed to produce oxide-dispersion strengthened (ODS) nickel- and iron-base superalloys for applications in the aerospace industry, MA has now been shown to be capable of synthesizing a variety of equilibrium and non-equilibrium alloy phases starting from blended elemental or prealloyed powders. The non-equilibrium phases synthesized include supersaturated solid solutions, metastable crystalline and quasicrystalline phases, nanostructures, and amorphous alloys. Recent advances in these areas and also on disordering of ordered intermetallics and mechanochemical synthesis of materials have been critically reviewed after discussing the process and process variables involved in MA. The often vexing problem of powder contamination has been analyzed and methods have been suggested to avoid/minimize it. The present understanding of the modeling of the MA process has also been discussed. The present and potential applications of MA are described. Wherever possible, comparisons have been made on the product phases obtained by MA with those of rapid solidification processing, another non-equilibrium processing technique.

Mechanical Alloying And Milling

5.1. Nanoalloys of Group 11 (Cu, Ag, Au) 865 5.1.1. Cu−Ag 866 5.1.2. Cu−Au 867 5.1.3. Ag−Au 870 5.1.4. Cu−Ag−Au 872 5.2. Nanoalloys of Group 10 (Ni, Pd, Pt) 872 5.2.1. Ni−Pd 872 * To whom correspondence should be addressed. Phone: +39010 3536214. Fax:+39010 311066. E-mail: ferrando@fisica.unige.it. † Universita di Genova. ‡ Argonne National Laboratory. § University of Birmingham. | As of October 1, 2007, Chemical Sciences and Engineering Division. Volume 108, Number 3

Nanoalloys: From Theory to Applications of Alloy Clusters and Nanoparticles

Nanostructured materials: basic concepts and microstructure☆

Metastasis, the dissemination and growth of neoplastic cells in an organ distinct from that in which they originated, is the most common cause of death in cancer patients. This is particularly true for pancreatic cancers, where most patients are diagnosed with metastatic disease and few show a sustained response to chemotherapy or radiation therapy. Whether the dismal prognosis of patients with pancreatic cancer compared to patients with other types of cancer is a result of late diagnosis or early dissemination of disease to distant organs is not known. Here we rely on data generated by sequencing the genomes of seven pancreatic cancer metastases to evaluate the clonal relationships among primary and metastatic cancers. We find that clonal populations that give rise to distant metastases are represented within the primary carcinoma, but these clones are genetically evolved from the original parental, non-metastatic clone. Thus, genetic heterogeneity of metastases reflects that within the primary carcinoma. A quantitative analysis of the timing of the genetic evolution of pancreatic cancer was performed, indicating at least a decade between the occurrence of the initiating mutation and the birth of the parental, non-metastatic founder cell. At least five more years are required for the acquisition of metastatic ability and patients die an average of two years thereafter. These data provide novel insights into the genetic features underlying pancreatic cancer progression and define a broad time window of opportunity for early detection to prevent deaths from metastatic disease.

SF-010-4 Distant metastasis occurs late during the genetic evolution of pancreatic cancer

We studied two elementary microstructure evolution events taking place at a multiple-twin triple junction (TJ) in Si by means of molecular dynamics simulations with the Stillinger–Weber empirical potential. Starting from a relaxed configuration, we inserted a fourth grain in the TJ location and determined the critical radius and the instability mode by which the central grain disappears by progressively shrinking. In a second set of simulations, we introduced a microcrack in the grain boundary plane and made it advance towards the TJ under the effect of the external loading. A kind of brittle–ductile transition is observed when the fracture changes from intergranular to intragranular.

Microstructure evolution at a triple junction in polycrystalline silicon

A biophysical model of cell evolution after cytotoxic treatments: Damage, repair and cell response.

Surface ordering of molecular structures by dispersion forces

We study the nucleation of carbon nanotubes based on the hypothesis that a cylindrical seed can be formed by the spontaneous rolling of a small graphite fragment under thermal fluctuations. We calculate the vibrational spectra of fragments of different sizes by means of a tight-binding model, and compare the spectra to that of an infinite graphite sheet, as a function of temperature. The spectra of finite-size fragments contain an increasing density of low-frequency, large amplitude modes with increasing temperature; it is shown that such modes tend to fold over the fragment into a cylindrical shape. Finally, direct tight-binding molecular-dynamics simulations of the high-temperature fluctuation of parallel graphite fragments demonstrate that nanotube seeds closed at one end can spontaneously form.

Vibrational modes of graphitic fragments and the nucleation of carbon nanotubes

The mechanics of fiber bundles has been largely investigated in order to understand their complex failure modes. Under a mechanical load, the fibers fail progressively while the load is redistributed among the unbroken fibers. The classical fiber bundle model captures the most important features of this rupture process. On the other hand, the homogenization techniques are able to evaluate the stiffness degradation of bulk solids with a given population of cracks. However, these approaches are inadequate to determine the effective response of a degraded bundle where breaks are induced by non-mechanical actions. Here, we propose a method to analyze the behavior of a fiber bundle, undergoing a random distribution of breaks, by considering the intrinsic response of the fibers and the visco-elastic interactions among them. We obtain analytical solutions for simple configurations, while the most general cases are studied by Monte Carlo simulations. We find that the degradation of the effective bundle stiffness can be described by two scaling regimes: a first exponential regime for a low density of breaks, followed by a power-law regime at increasingly higher break density. For both regimes, we find analytical effective expressions described by specific scaling exponents.

Fabrizio Cleri

Papers

Microstructure evolution at a triple junction in polycrystalline silicon

A biophysical model of cell evolution after cytotoxic treatments: Damage, repair and cell response.

Surface ordering of molecular structures by dispersion forces

Vibrational modes of graphitic fragments and the nucleation of carbon nanotubes

Stochastic mechanical degradation of multi-cracked fiber bundles with elastic and viscous interactions.