Calculations of the properties of self-interstitials and vacancies in the face-centred cubic metals Cu, Ag and Au

Atomistic Mechanisms of Binary Alloy Surface Segregation from Nanoseconds to Seconds Using Accelerated Dynamics

Although the equilibrium composition of many alloy surfaces is well understood, the rate of transient surface segregation during annealing is not known, despite its crucial effect on alloy corrosion and catalytic reactions occurring on overlapping timescales. In this work, CuNi bimetallic alloys representing (100) surface facets are annealed in vacuum using atomistic simulations to observe the effect of vacancy diffusion on surface separation. We employ multi-timescale methods to sample the early transient, intermediate, and equilibrium states of slab surfaces during the separation process, including standard MD as well as three methods to perform atomistic, long-time dynamics: parallel trajectory splicing (ParSplice), adaptive kinetic Monte Carlo (AKMC), and kinetic Monte Carlo (KMC). From nanosecond (ns) to second timescales, our multiscale computational methodology can observe rare stochastic events not typically seen with standard MD, closing the gap between computational and experimental timescales for surface segregation. Rapid diffusion of a vacancy to the slab is resolved by all four methods in tens of nanoseconds. Stochastic re-entry of vacancies into the subsurface, however, is only seen on the microsecond timescale in the two KMC methods. Kinetic vacancy trapping on the surface and its effect on the segregation rate are discussed. The equilibrium composition profile of CuNi after segregation during annealing is estimated to occur on a timescale of seconds as determined by KMC, a result directly comparable to nanoscale experiments.

Optimization and validation of a deep learning CuZr atomistic potential: Robust applications for crystalline and amorphous phases with near-DFT accuracy

We show that a deep-learning neural network potential (DP) based on density functional theory (DFT) calculations can well describe Cu-Zr materials, an example of a binary alloy system, that can coexist in as ordered intermetallic and as an amorphous phase. The complex phase diagram for Cu-Zr makes it a challenging system for traditional atomistic force-fields that cannot accurately describe the different properties and phases. Instead, we show that a DP approach using a large database with ∼300k configurations can render results generally on par with DFT. The training set includes configurations of pristine and bulk elementary metals and intermetallic structures in the liquid and solid phases in addition to slab and amorphous configurations. The DP model was validated by comparing bulk properties such as lattice constants, elastic constants, bulk moduli, phonon spectra, and surface energies to DFT values for identical structures. Furthermore, we contrast the DP results with values obtained using well-established two embedded atom method potentials. Overall, our DP potential provides near DFT accuracy for the different Cu-Zr phases but with a fraction of its computational cost, thus enabling accurate computations of realistic atomistic models, especially for the amorphous phase.

Near transferable phenomenological n-body potentials for noble metals

We present a semi-empirical model of cohesion in noble metals with suitable parameters reproducing a selected set of experimental properties of perfect and defective lattices in noble metals. It consists of two short-range, n-body terms accounting respectively for attractive and repulsive interactions, the former deriving from the second moment approximation of the tight-binding scheme and the latter from the gas approximation of the kinetic energy of electrons. The stability of the face centred cubic versus the hexagonal compact stacking is obtained via a long-range, pairwise function of customary use with ionic pseudo-potentials. Lattice dynamics, molecular statics, molecular dynamics and nudged elastic band calculations show that, unlike previous potentials, this cohesion model reproduces and predicts quite accurately thermodynamic properties in noble metals. In particular, computed surface energies, largely underestimated by existing empirical cohesion models, compare favourably with measured values, whereas predicted unstable stacking-fault energy profiles fit almost perfectly ab initio evaluations from the literature. All together the results suggest that this semi-empirical model is nearly transferable.