Multiple time scale simulations of metal crystal growth reveal the importance of multiatom surface processes

Atomistic mechanisms of phase nucleation and propagation in a model two-dimensional system

We present a computational study on the solid–solid phase transition of a model two-dimensional system between hexagonal and square phases under pressure. The atomistic mechanism of phase nucleation and propagation are determined using solid-state Dimer and nudged elastic band (NEB) methods. The Dimer is applied to identify the saddle configurations and NEB is applied to generate the transition minimum energy path (MEP) using the outputs of Dimer. Both the atomic and cell degrees of freedom are used in saddle search, allowing us to capture the critical nuclei with relatively small supercells. It is found that the phase nucleation in the model material is triggered by the localized shear deformation that comes from the relative shift between two adjacent atomic layers. In addition to the conventional layer-by-layer phase propagation, an interesting defect-assisted low barrier propagation path is identified in the hexagonal to square phase transition. The study demonstrates the significance of using the Dimer method in exploring unknown transition paths without a priori assumption. The results of this study also shed light on phase transition mechanisms of other solid-state and colloidal systems.

Island-size selectivity during 2D Ag island coarsening on Ag(111)

We report on the early stages of submonolayer Ag island coarsening on the Ag(111) surface carried out using kinetic Monte Carlo simulations for several temperatures. Our simulations were performed using a very large database of processes identified by their local environment and whose activation barriers were calculated using the semi-empirical interaction potentials based on the embedded-atom method. We find that during the early stages, coarsening proceeds as a sequence of selected island sizes, creating peaks and valleys in the island-size distribution. This island-size selectivity is independent of initial conditions and results from the formation of kinetically stable islands for certain sizes as dictated by the relative energetics of edge atom detachment/attachment processes together with the large activation barrier for kink detachment. Our results indicate that by tuning the growth temperature it is possible to enhance the island-size selectivity.

Efficient annealing of radiation damage near grain boundaries via interstitial emission

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.

Off-lattice self-learning kinetic Monte Carlo: application to 2D cluster diffusion on the fcc(111) surface

We report developments of the kinetic Monte Carlo (KMC) method with improved accuracy and increased versatility for the description of atomic diffusivity on metal surfaces. The on-lattice constraint built into our recently proposed self-learning KMC (SLKMC) (Trushin et al 2005 Phys. Rev. B 72 115401) is released, leaving atoms free to occupy 'off-lattice' positions to accommodate several processes responsible for small-cluster diffusion, periphery atom motion and heteroepitaxial growth. This technique combines the ideas embedded in the SLKMC method with a new pattern-recognition scheme fitted to an off-lattice model in which relative atomic positions are used to characterize and store configurations. Application of a combination of the 'drag' and the repulsive bias potential (RBP) methods for saddle point searches allows the treatment of concerted cluster, and multiple- and single-atom, motions on an equal footing. This tandem approach has helped reveal several new atomic mechanisms which contribute to cluster migration. We present applications of this off-lattice SLKMC to the diffusion of 2D islands of Cu (containing 2-30 atoms) on Cu and Ag(111), using the interatomic potential from the embedded-atom method. For the hetero-system Cu/Ag(111), this technique has uncovered mechanisms involving concerted motions such as shear, breathing and commensurate-incommensurate occupancies. Although the technique introduces complexities in storage and retrieval, it does not introduce noticeable extra computational cost.

Adaptive kinetic Monte Carlo for first-principles accelerated dynamics

The adaptive kinetic Monte Carlo method uses minimum-mode following saddle point searches and harmonic transition state theory to model rare-event, state-to-state dynamics in chemical and material systems. The dynamical events can be complex, involve many atoms, and are not constrained to a grid-relaxing many of the limitations of regular kinetic Monte Carlo. By focusing on low energy processes and asserting a minimum probability of finding any saddle, a confidence level is used to describe the completeness of the calculated event table for each state visited. This confidence level provides a dynamic criterion to decide when sufficient saddle point searches have been completed. The method has been made efficient enough to work with forces and energies from density functional theory calculations. Finding saddle points in parallel reduces the simulation time when many computers are available. Even more important is the recycling of calculated reaction mechanisms from previous states along the dynamics. For systems with localized reactions, the work required to update the event table from state to state does not increase with system size. When the reaction barriers are high with respect to the thermal energy, first-principles simulations over long time scales are possible.

Solvent-induced acceleration of the rate of activation of a molecular reaction

An increase in the rates of activated processes with the coupling to the solvent has long been predicted through the phenomenological Langevin equation in the weak coupling regime. However, its direct observation in particle-based models has been elusive because the coupling typically places the processes in the spacial-diffusion limited regime wherein rates decrease with increasing friction. In this work, the forward and backward reaction rates of the LiNC<==>LiCN isomerization reaction in a bath of argon atoms at various densities have been calculated directly using molecular dynamics trajectories. The so-called Kramers turnover in the rate with microscopic friction is clearly visible, thus providing direct and unambiguous evidence for the energy-diffusion regime in which rates increase with friction.

Effects of long jumps, reversible aggregation, and Meyer-Neldel rule on submonolayer epitaxial growth

We demonstrate, using kinetic Monte Carlo simulations of submonolayer epitaxial growth, that long jumps and reversible aggregation have a major impact on the evolution of island morphologies. Long jumps are responsible for a supra-Arrhenius behavior of the effective diffusion coefficient as the attachment and detachment kinetics give rise to a bimodal island size distribution that depends on temperature and long jump extent limits. As the islands density increases with temperature, the average size of stable islands reaches a maximum before decreasing. We have also observed that the diffusion coefficient cannot be used alone to predict the evolution of island sizes and morphologies, the relative rate of each process having a major importance. Our theoretical developments are of direct relevance for materials systems such as Au, Pd, Ag, Cu, Ni, H/Si , H/W(110), Co/Ru , and Co/Ru(S), that are known for exhibiting a compensation effect that cannot be contained within experimental uncertainties.

Oxygen-deficient perovskites: linking structure, energetics and ion transport

The present review focuses on links between structure, energetics and ion transport in oxygen-deficient perovskite oxides, ABO(3-delta). The perfect long-range order, convenient for interpretations of the structure and properties of ordered materials, is evidently not present in disordered materials and highly defective perovskite oxides are spatially inhomogeneous on an intermediate length scale. Although this makes a fundamental description of these and other disordered materials very difficult, it is becoming increasingly clear that this complexity is often essential for the functional properties. In the present review we advocate a potential energy barrier description of the disordered state in which the possible local (or inherent) structures are seen to correspond to separate local minima on the potential energy surface. We interpret the average structure observed experimentally at any temperature as a time and spatial average of the different local structures which are energetically accessible. The local structure is largely affected by preferences for certain polyhedron coordinations and the oxidation state stability of the transition metals, and the strong long-range electrostatic interactions present in non-stoichiometric oxides imply that only a small fraction of the local energy minima on the potential energy surface are accessible at most temperatures. We will show that models neglecting the spatial inhomogeneity and thus the local structure serve as useful empirical tools for particular purposes, e.g. for understanding the main features of the complex redox properties that are so crucial for many applications of these oxides. The short-range order is on the other hand central for understanding ionic transport. Oxide ion transport involves the transformation of one energetically accessible local structure into another. Thus, strongly correlated transport mechanisms are expected; in addition to the movement of the oxygen ions giving rise to the transport, other ions are involved and even the A and B atoms move appreciably in a cooperative fashion along the transition path. Such strongly correlated or collective ionic migration mechanisms should be considered for fast oxide ion conductors in general and in particular for systems forming superstructures at low temperatures. Structural criteria for fast ion conduction are discussed. A high density of low-lying local energy minima is certainly a prerequisite and for perovskite-related A(2)B(2)O(5) oxides, those containing B atoms that have energetic preference for tetrahedral coordination geometry are especially promising.