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  1. ParSplice, Version 1

    The ParSplice code implements the Parallel Trajectory Splicing algorithm described in [1]. This method is part of the Accelerated Molecular Dynamics family of techniques developed in Los Alamos National Laboratory over the last 16 years. These methods aim at generating high-quality trajectories of ensembles of atoms in materials. ParSplice uses multiple independent replicas of the system in order to parallelize the generation of such trajectories in the time domain, enabling simulations of systems of modest size over very long timescales. ParSplice includes capabilities to store configurations of the system, to generate and distribute tasks across a large number of processors,more » and to harvest the results of these tasks to generate long trajectories. ParSplice is a management layer that orchestrate large number of calculations, but it does not perform the actual molecular dynamics itself; this is done by external molecular dynamics engines. [1] Danny Perez, Ekin D Cubuk, Amos Waterland, Efthimios Kaxiras, Arthur F Voter, Long-time dynamics through parallel trajectory splicing, Journal of chemical theory and computation 12, 18 (2015)« less
  2. Atomistic simulation methods for long-time dynamics in materials for nuclear energy systems

    Many important processes in materials systems are intrinsically atomistic in nature but involve time scales that span many orders of magnitude, thus exceeding what can be directly simulated using molecular dynamics. This is especially true for materials in nuclear energy applications, in which defects created by collision cascades on the femtosecond-picosecond time scale cause microstructural changes that continue to evolve for years, in many cases leading to failure of the material. In this chapter, we review atomistic methods for reaching long time scales in systems like these. These accelerated molecular dynamics and adaptive kinetic Monte Carlo methods exploit the infrequent-eventmore » nature of the diffusive events that comprise this long-time evolution. In favorable cases, these methods can predict state-to-state evolution that approximates what would result from an extremely long molecular dynamics simulation, and the most accurate of the methods can do this to arbitrary accuracy. We present some examples of applications of these methods to problems relevant to nuclear energy materials, the subject of this volume. We then discuss situations that are difficult for the methods, causing them to be less efficient, and we conclude with a short list of the most pressing issues in the further development of these approaches to make them as powerful and predictive as possible for realistic problems.« less
  3. Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification

    Here, a massively parallel method to build large transition rate matrices from temperature-accelerated molecular dynamics trajectories is presented. Bayesian Markov model analysis is used to estimate the expected residence time in the known state space, providing crucial uncertainty quantification for higher-scale simulation schemes such as kinetic Monte Carlo or cluster dynamics. The estimators are additionally used to optimize where exploration is performed and the degree of temperature acceleration on the fly, giving an autonomous, optimal procedure to explore the state space of complex systems. The method is tested against exactly solvable models and used to explore the dynamics of C15more » interstitial defects in iron. Our uncertainty quantification scheme allows for accurate modeling of the evolution of these defects over timescales of several seconds.« less
  4. Speculation and replication in temperature accelerated dynamics

    Accelerated Molecular Dynamics (AMD) is a class of MD-based algorithms for the long-time scale simulation of atomistic systems that are characterized by rare-event transitions. Temperature-Accelerated Dynamics (TAD), a traditional AMD approach, hastens state-to-state transitions by performing MD at an elevated temperature. Recently, Speculatively-Parallel TAD (SpecTAD) was introduced, allowing the TAD procedure to exploit parallel computing systems by concurrently executing in a dynamically generated list of speculative future states. Although speculation can be very powerful, it is not always the most efficient use of parallel resources. In this paper, we compare the performance of speculative parallelism with a replica-based technique, similarmore » to the Parallel Replica Dynamics method. A hybrid SpecTAD approach is also presented, in which each speculation process is further accelerated by a local set of replicas. Finally and overall, this work motivates the use of hybrid parallelism whenever possible, as some combination of speculation and replication is typically most efficient.« less
    Cited by 1
  5. Long-time molecular dynamics simulations on massively parallel platforms: A comparison of parallel replica dynamics and parallel trajectory splicing

    Molecular dynamics (MD) is one of the most widely used techniques in computational materials science. By providing fully resolved trajectories, it allows for a natural description of static, thermodynamic, and kinetic properties. A major hurdle that has hampered the use of MD is the fact that the timescales that can be directly simulated are very limited, even when using massively parallel computers. We compare two time-parallelization approaches, parallel replica dynamics (ParRep) and parallel trajectory splicing (ParSplice), that were specifically designed to address this issue for rare event systems by leveraging parallel computing resources. Using simulations of the relaxation of smallmore » disordered platinum nanoparticles, a comparative performance analysis of the two methods is presented. Finally, the results show that ParSplice can significantly outperform ParRep in the common case where the trajectory remains trapped for a long time within a region of configuration space but makes rapid structural transitions within this region.« less
    Cited by 1
  6. Discovering mechanisms relevant for radiation damage evolution

    he response of a material to irradiation is a consequence of the kinetic evolution of defects produced during energetic damage events. Thus, accurate predictions of radiation damage evolution require knowing the atomic scale mechanisms associated with those defects. Atomistic simulations are a key tool in providing insight into the types of mechanisms possible. Further, by extending the time scale beyond what is achievable with conventional molecular dynamics, even greater insight can be obtained. Here, we provide examples in which such simulations have revealed new kinetic mechanisms that were not obvious before performing the simulations. We also demonstrate, through the couplingmore » with higher level models, how those mechanisms impact experimental observables in irradiated materials. Lastly, we discuss the importance of these types of simulations in the context of predicting material behavior.« less
  7. Cluster analysis of accelerated molecular dynamics simulations: A case study of the decahedron to icosahedron transition in Pt nanoparticles

    Modern molecular-dynamics-based techniques are extremely powerful to investigate the dynamical evolution of materials. With the increase in sophistication of the simulation techniques and the ubiquity of massively parallel computing platforms, atomistic simulations now generate very large amounts of data, which has to be carefully analyzed in order to reveal key features of the underlying trajectories, including the nature and characteristics of the relevant reaction pathways. We show that clustering algorithms, such as the Perron Cluster Cluster Analysis, can provide reduced representations that greatly facilitate the interpretation of complex trajectories. To illustrate this point, clustering tools are used to identify themore » key kinetic steps in complex Accelerated Molecular Dynamics trajectories exhibiting shape uctuations in Pt nanoclusters. This analysis provides an easily-interpretable coarse representation of the reaction pathways in terms of a handful of clusters, in contrast to the raw trajectory that contains thousands of unique states and tens of thousands of transitions.« less
  8. Evidence for percolation diffusion of cations and reordering in disordered pyrochlore from accelerated molecular dynamics

    Diffusion in complex oxides is critical to ionic transport, radiation damage evolution, sintering, and aging. In complex oxides such as pyrochlores, anionic diffusion is dramatically affected by cation disorder. However, little is known about how disorder influences cation transport. Here, we report results from classical and accelerated molecular dynamics simulations of vacancy-mediated cation diffusion in Gd 2Ti 2O 7 pyrochlore, on the microsecond timescale. We find that diffusion is slow at low levels of disorder, while higher disorder allows for fast diffusion, which is then accompanied by antisite annihilation and reordering, and thus a slowing of cation transport. Cation diffusivitymore » is therefore not constant, but decreases as the material reorders. We also show that fast cation diffusion is triggered by the formation of a percolation network of antisites. This is in contrast with observations from other complex oxides and disordered media models, suggesting a fundamentally different relation between disorder and mass transport.« less
  9. Accelerating ring-polymer molecular dynamics with parallel-replica dynamics

    Nuclear quantum effects are important for systems containing light elements, and the effects are more prominent in the low temperature regime where the dynamics also becomes sluggish. We show that parallel replica (ParRep) dynamics, an accelerated molecular dynamics approach for infrequent-event systems, can be effectively combined with ring-polymer molecular dynamics, a semiclassical trajectory approach that gives a good approximation to zero-point and tunneling effects in activated escape processes. The resulting RP-ParRep method is a powerful tool for reaching long time scales in complex infrequent-event systems where quantum dynamics are important. Two illustrative examples, symmetric Eckart barrier crossing and interstitial heliummore » diffusion in Fe and Fe–Cr alloy, are presented to demonstrate the accuracy and long-time scale capability of this approach.« less
  10. Growth rate effects on the formation of dislocation loops around deep helium bubbles in Tungsten

    Here, the growth process of spherical helium bubbles located 6 nm below a (100) surface is studied using molecular dynamics and parallel replica dynamics simulations, over growth rates from 10 6 to 10 12 helium atoms per second. Slower growth rates lead to a release of pressure and lower helium content as compared with fast growth cases. In addition, at slower growth rates, helium bubbles are not decorated by multiple dislocation loops, as these tend to merge or emit given sufficient time. At faster rates, dislocation loops nucleate faster than they can emit, leading to a more complicated dislocation structuremore » around the bubble.« less
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