Publications by authors named "Vasily V Bulatov"

For millennia, humans have exploited the natural property of metals to get stronger or harden when mechanically deformed. Ultimately rooted in the motion of dislocations, mechanisms of metal hardening have remained in the cross-hairs of physical metallurgists for over a century. Here, we performed atomistic simulations at the limits of supercomputing that are sufficiently large to be statistically representative of macroscopic crystal plasticity yet fully resolved to examine the origins of metal hardening at its most fundamental level of atomic motion.

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Ordinarily, the strength and plasticity properties of a metal are defined by dislocations-line defects in the crystal lattice whose motion results in material slippage along lattice planes. Dislocation dynamics models are usually used as mesoscale proxies for true atomistic dynamics, which are computationally expensive to perform routinely. However, atomistic simulations accurately capture every possible mechanism of material response, resolving every "jiggle and wiggle" of atomic motion, whereas dislocation dynamics models do not.

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The computational efficiency of stochastic simulation algorithms is notoriously limited by the kinetic trapping of the simulated trajectories within low energy basins. Here we present a new method that overcomes kinetic trapping while still preserving exact statistics of escape paths from the trapping basins. The method is based on path factorization of the evolution operator and requires no prior knowledge of the underlying energy landscape.

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Dislocation mobility is a fundamental material property that controls strength and ductility of crystals. An important measure of dislocation mobility is its Peierls stress, i.e.

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We present an efficient method for Monte Carlo simulations of diffusion-reaction processes. Introduced by us in a previous paper [Phys. Rev.

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We present a novel Monte Carlo algorithm for N diffusing finite particles that react on collisions. Using the theory of first-passage processes and time dependent Green's functions, we break the difficult N-body problem into independent single- and two-body propagations circumventing numerous diffusion hops used in standard Monte Carlo simulations. The new algorithm is exact, extremely efficient, and applicable to many important physical situations in arbitrary integer dimensions.

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At the microscopic scale, the strength of a crystal derives from the motion, multiplication and interaction of distinctive line defects called dislocations. First proposed theoretically in 1934 (refs 1-3) to explain low magnitudes of crystal strength observed experimentally, the existence of dislocations was confirmed two decades later. Much of the research in dislocation physics has since focused on dislocation interactions and their role in strain hardening, a common phenomenon in which continued deformation increases a crystal's strength.

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We develop a general theoretical framework for the recently proposed importance sampling method for enhancing the efficiency of rare-event simulations [W. Cai, M. H.

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The motion of dislocations in response to stress dictates the mechanical behaviour of materials. However, it is not yet possible to directly observe dislocation motion experimentally at the atomic level. Here, we present the first observations of the long-hypothesized kink-pair mechanism in action using atomistic simulations of dislocation motion in iron.

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Direct atomistic simulations of dislocation multiplication in fcc aluminum reveal an unexpected mechanism, in which a Frank-Read source emits dislocations with Burgers vectors different from that of the source itself. The mechanism is traced to a spontaneous nucleation of partial dislocation loops within the stacking fault. Understanding and a quantitative description of this unusual process are achieved through the development of a continuum model for dislocation nucleation based on the coarse-grained dislocation dynamics approach and a minimal amount of atomistic input.

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We present an importance sampling technique for enhancing the efficiency of sampling rare transition events in Markov processes. Our approach is based on the design of an importance function by which the absolute probability of sampling a successful transition event is significantly enhanced, while preserving the relative probabilities among different successful transition paths. The method features an iterative stochastic algorithm for determining the optimal importance function.

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We show that, contrary to the prevailing perception, dislocations can become more mobile by zipping together to form junctions. In a series of direct atomistic simulations, the critical stress to move a junction network in a [110] plane of bcc molybdenum is found to be always smaller ( approximately 50%) than that required to move isolated dislocations. Our data support a previously proposed hypothesis about the nature of anomalous slip in bcc transition metals, yet offer a different atomistic mechanism for conservative motion of screw dislocation networks.

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