We evaluate the ability of the embedded-atom method ͑EAM͒ potentials and the tight-binding ͑TB͒ method to predict reliably energies and stability of nonequilibrium structures by taking Cu as a model material. Two EAM potentials are used here. One is constructed in this work by using more fitting parameters than usual and including ab initio energies in the fitting database. The other potential was constructed previously using a traditional scheme. Excellent agreement is observed between ab initio, TB, and EAM results for the energies and stability of several nonequilibrium structures of Cu, as well as for energies along deformation paths between different structures. We conclude that not only TB calculations but also EAM potentials can be suitable for simulations in which correct energies and stability of different atomic configurations are essential, at least for Cu. The bcc, simple cubic, and diamond structures of Cu were identified as elastically unstable, while some other structures ͑e.g., hcp and 9R͒ are metastable. As an application of this analysis, nonequilibrium structures of epitaxial Cu films on ͑001͒-oriented fcc or bcc substrates are evaluated using a simple model and atomistic simulations with an EAM potential. In agreement with experimental data, the structure of the film can be either deformed fcc or deformed hcp. The bcc structure cannot be stabilized by epitaxial constraints.

I derive a general method for accelerating the molecular-dynamics (MD) simulation of infrequent events in solids. A bias potential (DV b) raises the energy in regions other than the transition states between potential basins. Transitions occur at an accelerated rate and the elapsed time becomes a statistical property of the system. DV b can be constructed without knowing the location of the transition states and implementation requires only first derivatives. I examine the diffusion mechanisms of a 10-atom Ag cluster on the Ag(111) surface using a 220 ms hyper-MD simulation.

Although grain boundaries can serve as effective sinks for radiation-induced defects such as interstitials and vacancies, the atomistic mechanisms leading to this enhanced tolerance are still not well understood. With the use of three atomistic simulation methods, we investigated defect-grain boundary interaction mechanisms in copper from picosecond to microsecond time scales. We found that grain boundaries have a surprising "loading-unloading" effect. Upon irradiation, interstitials are loaded into the boundary, which then acts as a source, emitting interstitials to annihilate vacancies in the bulk. This unexpected recombination mechanism has a much lower energy barrier than conventional vacancy diffusion and is efficient for annihilating immobile vacancies in the nearby bulk, resulting in self-healing of the radiation-induced damage.

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We present a method for accelerating dynamic simulations of activated processes in solids. By raising the temperature, but allowing only those events that should occur at the original temperature, the time scale of a simulation is extended by orders of magnitude compared to ordinary molecular dynamics, while preserving the correct dynamics at the original temperature. The main assumption behind the method is harmonic transition state theory. Importantly, the method does not require any prior knowledge about the transition mechanisms. As an example, the method is applied to a study of surface diffusion, where concerted processes play a key role. In the example, times of hours are achieved at a temperature of 150 K.

For infrequent-event systems, transition state theory ͑TST͒ is a powerful approach for overcoming the time scale limitations of the molecular dynamics ͑MD͒ simulation method, provided one knows the locations of the potential-energy basins ͑states͒ and the TST dividing surfaces ͑or the saddle points͒ between them. Often, however, the states to which the system will evolve are not known in advance. We present a new, TST-based method for extending the MD time scale that does not require advanced knowledge of the states of the system or the transition states that separate them. The potential is augmented by a bias potential, designed to raise the energy in regions other than at the dividing surfaces. State to state evolution on the biased potential occurs in the proper sequence, but at an accelerated rate with a nonlinear time scale. Time is no longer an independent variable, but becomes a statistically estimated property that converges to the exact result at long times. The long-time dynamical behavior is exact if there are no TST-violating correlated dynamical events, and appears to be a good approximation even when this condition is not met. We show that for strongly coupled ͑i.e., solid state͒ systems, appropriate bias potentials can be constructed from properties of the Hessian matrix. This new ''hyper-MD'' method is demonstrated on two model potentials and for the diffusion of a Ni atom on a Ni͑100͒ terrace for a duration of 20 s.

▪ Abstract  Obtaining a good atomistic description of diffusion dynamics in materials has been a daunting task owing to the time-scale limitations of the molecular dynamics method. We discuss promising new methods, derived from transition state theory, for accelerating molecular dynamics simulations of these infrequent-event processes. These methods, hyperdynamics, parallel replica dynamics, temperature-accelerated dynamics, and on-the-fly kinetic Monte Carlo, can reach simulation times several orders of magnitude longer than direct molecular dynamics while retaining full atomistic detail. Most applications so far have involved surface diffusion and growth, but it is clear that these methods can address a wide range of materials problems.

Although molecular-dynamics simulations can be parallelized effectively to treat large systems ͑10 6-10 8 atoms͒, to date the power of parallel computers has not been harnessed to make analogous gains in time scale. I present a simple approach for infrequent-event systems that extends the time scale with high parallel efficiency. Integrating a replica of the system independently on each processor until the first transition occurs gives the correct transition-time distribution, and hence the correct dynamics. I obtain Ͼ90% efficiency simulating Cu͑100͒ surface vacancy diffusion on 15 processors. ͓S0163-1829͑98͒51420-8͔