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

UV-Visible ار راد ن .د TiO2 ( تیفرظ راون مان هب نورتکلا یاراد یژرنا زارت لماش VB و ) رگید زارت ی یژرنا اب ( ییاناسر راون مان هب نورتکلا زا یلاخ و رتلااب VB یم ) .دشاب ت ود نیا نیب یژرنا توافت یژرنا فاکش زار ، پگ دناب هدیمان یم .دوش هک ینامز زا نورتکلا لاقتنا VB هب VB یم ماجنا دریگ ، TiO2 اب ودح یژرنا بذج د ev 2 / 3 ، نورتکلا تفج کی دیلوت یم هرفح .دیامن و نورتکلا هرفح ی نا اب هدش دیلوت یم کرتشم حطس هب لاقت ثعاب دناوت شنکاو ماجنا اه یی ددرگ . TiO2 دربراک ،دراد یدایز یاه هلمج زا یم ناوت اوه یگدولآ هیفصت یارب (CO2) و بآ و ... نآ زا هدافتسا درک .

Advanced Nanoarchitectures for Solar Photocatalytic Applications

Intermolecular And Surface Forces

Metadynamics is a powerful algorithm that can be used both for reconstructing the free energy and for accelerating rare events in systems described by complex Hamiltonians, at the classical or at the quantum level. In the algorithm the normal evolution of the system is biased by a history-dependent potential constructed as a sum of Gaussians centered along the trajectory followed by a suitably chosen set of collective variables. The sum of Gaussians is exploited for reconstructing iteratively an estimator of the free energy and forcing the system to escape from local minima. This review is intended to provide a comprehensive description of the algorithm, with a focus on the practical aspects that need to be addressed when one attempts to apply metadynamics to a new system: (i) the choice of the appropriate set of collective variables; (ii) the optimal choice of the metadynamics parameters and (iii) how to control the error and ensure convergence of the algorithm.

http://iopscience.iop.org/article/10.1088/0034-4885/71/12/126601/pdf

Metadynamics: a method to simulate rare events and reconstruct the free energy in biophysics, chemistry and material science

Field and laboratory observations show that crystals commonly form by the addition and attachment of particles that range from multi-ion complexes to fully formed nanoparticles. The particles involved in these nonclassical pathways to crystallization are diverse, in contrast to classical models that consider only the addition of monomeric chemical species. We review progress toward understanding crystal growth by particle-attachment processes and show that multiple pathways result from the interplay of free-energy landscapes and reaction dynamics. Much remains unknown about the fundamental aspects, particularly the relationships between solution structure, interfacial forces, and particle motion. Developing a predictive description that connects molecular details to ensemble behavior will require revisiting long-standing interpretations of crystal formation in synthetic systems, biominerals, and patterns of mineralization in natural environments.

/pdf/crystallization-by-particle-attachment-in-synthetic-biogenic-2voi5gdwxm.pdf

Crystallization by particle attachment in synthetic, biogenic, and geologic environments

Monte Carlo methods are utilized as computational tools in many areas of chemical physics. In this paper, we present the theoretical basis for a dynamical Monte Carlo method in terms of the theory of Poisson processes. We show that if: (1) a ‘‘dynamical hierarchy’’ of transition probabilities is created which also satisfy the detailed‐balance criterion; (2) time increments upon successful events are calculated appropriately; and (3) the effective independence of various events comprising the system can be achieved, then Monte Carlo methods may be utilized to simulate the Poisson process and both static and dynamic properties of model Hamiltonian systems may be obtained and interpreted consistently.

/pdf/theoretical-foundations-of-dynamical-monte-carlo-simulations-3k85uzfg02.pdf

Theoretical foundations of dynamical Monte Carlo simulations

We describe a theoretical study of the role of adsorbate interactions in island nucleation and growth, using Ag/Pt(111) heteroepitaxy as an example. From density-functional theory, we obtain the substrate-mediated Ag adatom pair interaction and we find that, past the short range, a repulsive ring is formed about the adatoms. The magnitude of the repulsion is comparable to the diffusion barrier. In kinetic Monte Carlo simulations, we find that the repulsive interactions lead to island densities over an order of magnitude larger than those predicted by nucleation theory and thus identify a severe limitation of its applicability.

/pdf/island-nucleation-in-thin-film-epitaxy-a-first-principles-sc3dfq3lz1.pdf

Island nucleation in thin-film epitaxy: A first-principles investigation

We use density functional theory to resolve the role of polyvinylpyrrolidone (PVP) in the shape-selective synthesis of Ag nanostructures. At the segment level, PVP binds more strongly to Ag(100) than Ag(111) because of a surface-sensitive balance between direct binding and van der Waals attraction. At the chain level, correlated segment binding leads to a strong preference for PVP bind to Ag(100). Our study underscores differences between small-molecule and polymeric structure-directing agents.

Adsorption of Polyvinylpyrrolidone on Ag Surfaces: Insight into a Structure-Directing Agent

We present a new method for accelerating molecular-dynamics simulations of infrequent events. The method targets simulation of systems that spend most of the time in local energy minima, with slow transitions in between, as is the case with low-temperature surface diffusion. The potential-energy surface is modified by adding a boost potential in regions close to the local minima, such that all transition rates are increased while relative rates are preserved. The boost potential is an empirical function determined by the deviation of the bond lengths of a specified set of atoms from equilibrium. The method requires no previous knowledge of the processes involved and it can be applied to a wide variety of interaction potentials. Application to the diffusion of Cu atoms on the Cu(100) surface using an embedded-atom potential yields correct rates for adatom hopping, exchange, as well as vacancy and dimer diffusion with speed-ups up to several orders of magnitude.

Accelerated molecular dynamics with the bond-boost method

Oriented attachment (OA) of nanocrystals is now widely recognized as a key process in the solution-phase growth of hierarchical nanostructures. However, the microscopic origins of OA remain unclear. We perform molecular dynamics simulations using a recently developed ReaxFF reactive force field to study the aggregation of various titanium dioxide (anatase) nanocrystals in vacuum and humid environments. In vacuum, the nanocrystals merge along their direction of approach, resulting in a polycrystalline material. By contrast, in the presence of water vapor the nanocrystals reorient themselves and aggregate via the OA mechanism to form a single or twinned crystal. They accomplish this by creating a dynamic network of hydrogen bonds between surface hydroxyls and surface oxygens of aggregating nanocrystals. We determine that OA is dominant on surfaces that have the greatest propensity to dissociate water. Our results are consistent with experiment, are likely to be general for aqueous oxide systems, and demonst...

Kristen A. Fichthorn

Papers

Theoretical foundations of dynamical Monte Carlo simulations

Island nucleation in thin-film epitaxy: A first-principles investigation

Adsorption of Polyvinylpyrrolidone on Ag Surfaces: Insight into a Structure-Directing Agent

Accelerated molecular dynamics with the bond-boost method

Mechanisms of oriented attachment of TiO2 nanocrystals in vacuum and humid environments: reactive molecular dynamics.