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

Confinement of matter on the nanometre scale can induce phase transitions not seen in bulk systems1. In the case of water, so-called drying transitions occur on this scale2,3,4,5 as a result of strong hydrogen-bonding between water molecules, which can cause the liquid to recede from nonpolar surfaces to form a vapour layer separating the bulk phase from the surface6. Here we report molecular dynamics simulations showing spontaneous and continuous filling of a nonpolar carbon nanotube with a one-dimensionally ordered chain of water molecules. Although the molecules forming the chain are in chemical and thermal equilibrium with the surrounding bath, we observe pulse-like transmission of water through the nanotube. These transmission bursts result from the tight hydrogen-bonding network inside the tube, which ensures that density fluctuations in the surrounding bath lead to concerted and rapid motion along the tube axis7,8,9. We also find that a minute reduction in the attraction between the tube wall and water dramatically affects pore hydration, leading to sharp, two-state transitions between empty and filled states on a nanosecond timescale. These observations suggest that carbon nanotubes, with their rigid nonpolar structures10,11, might be exploited as unique molecular channels for water and protons, with the channel occupancy and conductivity tunable by changes in the local channel polarity and solvent conditions.

Water conduction through the hydrophobic channel of a carbon nanotube

There is a special reason for reviewing this book at this time: it is the 50th edition of a compendium that is known and used frequently in most chemical and physical laboratories in many parts of the world. Surely, a publication that has been published for 56 years, withstanding the vagaries of science in this century, must have had something to offer. There is another reason: while the book is a standard fixture in most chemical and physical laboratories, including those in medical centers, it is not as frequently seen in the laboratories of physician's offices (those either in solo or group practice). I believe that the Handbook can be useful in those laboratories. One of the reasons, among others, is that the various basic items of information it offers may be helpful in new tests, either physical or chemical, which are continuously being published. The basic information may relate

Handbook of Chemistry and Physics

Gold is known as a shiny, yellow noble metal that does not tarnish, has a face centred cubic structure, is non-magnetic and melts at 1336 K. However, a small sample of the same gold is quite different, providing it is tiny enough: 10 nm particles absorb green light and thus appear red. The meltingtemperature decreases dramatically as the size goes down. Moreover, gold ceases to be noble, and 2–3 nm nanoparticles are excellent catalysts which also exhibit considerable magnetism. At this size they are still metallic, but smaller ones turn into insulators. Their equilibrium structure changes to icosahedral symmetry, or they are even hollow or planar, depending on size. The present tutorial review intends to explain the origin of this special behaviour of nanomaterials.

Size matters: why nanomaterials are different

http://kbose.weebly.com/uploads/1/0/4/9/10492046/force-distance_curves_by_atomic_force_microscopy_1.pdf

Force-distance curves by atomic force microscopy

1. G. Reichenauer and G. W. Scherer, Nitrogen sorption in aerogels, J. Non-Cryst. Solids 285 (2001) 167-174. 2. E. Kierlik and P. A. Monson and M. L. Rosinberg and L. Sarkisov and G. Tarjus, Capillary condensation in disordered porous materials: Hysteresis versus equilibrium behavior, Phys. Rev. Letts., (2001) 055701. 3. L. D. Gelb, Simulating Silica Aerogels with a Coarse-Grained Flexible Model and Langevin Dynamics, J. Phys. Chem. C 111 (2007) p. 15792-15802. 4. C. J. Brinker and G. W. Scherer, Sol-Gel Science, (1990, Acad. Press, San Diego) 5. M. J. De Oliveira and R. B. Griffiths, Lattice Gas Model of Multilayer Adsorption, Surf. Sci. 71 (1978) 687-694. 6. H. Asada, Multilayer Lattice Gas Model in the Quasichemical Approximation, Surf. Sci., 230 (1990) 323-328. 7. K. Huang, Statistical Mechanics, (1963, Wiley, New York.) 8. L. D. Gelb and K. E. Gubbins, Molecular Simulation of Capillary Phenomena in Controlled Pore Glasses, Fundamentals of Adsorption 7 (2001) p. 333-339. 9. M. Whittle and E. Dickinson, Brownian dynamics simulation of gelation in soft sphere systems with irreversible bond formation, Mol. Phys. 90 (1997) p. 739-757. We present results from simulations of gas adsorption in aerogels in which the flexibility of the gel matrix is treated explicitly. Low density aerogels have very low bulk moduli (generally in the range 1-100 bar), and display nontrivial mechanical deformations during adsorption and desorption processes, especially near to the capillary rise and desorption shoulder [1]. However, previous studies of adsorption in aerogels have invariably treated the gel structure as rigid [2].

Lev D. Gelb

Papers

Computational studies of gas adsorption in aerogels: The effects of gel flexibility on adsorptive behavior