Atomistic material behavior at extreme pressures

Abstract

Computer simulations are routinely performed to model the response of materials to extreme environments, such as neutron (or ion) irradiation. The latter involves high-energy collisions from which a recoiling atom creates a so-called atomic displacement cascade. These cascades involve coordinated motion of atoms in the form of supersonic shockwaves. These shockwaves are characterized by local atomic pressures 415 GPa and interatomic distances o 2 Å. Similar pressures and interatomic distances are observed in other extreme environment, including short-pulse laser ablation, high-impact ballistic collisions and diamond anvil cells. Displacement cascade simulations using four different force fields, with initial kinetic energies ranging from 1 to 40 keV, show that there is a direct relationship between these high-pressure states and stable defect production. An important shortcoming in the modeling of interatomic interactions at these short distances, which in turn determines final defect production, is brought to light. INTRODUCTIONAs scientific computing becomes evermore ubiquitous, it is common practice to simulate the effect of extreme environments on materials using molecular dynamics (MD). The ability to capture a material's response atom by atom has helped understand and complement experiments. For example, thanks to MD, the thermodynamic processes that control the production of nanoparticules after pulsed laser irradiation are relatively well understood. 1 Notably, such computational results explain the Newton rings observed in experiments. 2,3 MD also led to a better understanding of the nature of the destructive shockwaves that follow high-energy impact 4-6 and the behavior of materials at high pressure in diamond anvil cells. 7-9 It can predict many properties, such as the Hugoniot, dislocation densities after impact and fracture behavior. In the case of neutron and ion irradiation, MD can be used to predict the evolution of ballistic collisions that occur, and the nature of primary damage produced by the high-energy recoils. 10 It can also shed light on a plethora of mechanisms that take place as the kinetic energy of the recoil is dissipated: fractal replacement sequences, 11 supersonic shockwaves, 12 sonic waves, 12 the formation of liquid-like regions and their recrystallization or amorphization. 13 The aim of many MD studies is to describe the mechanisms and general trends, not to make precise predictions. However, as the scientific community moves towards materials by design and systematic computational characterization, increasingly precise and accurate models are required. In the case of atomistic modeling, methods that explicitly account for electronic structure, such as ab initio MD, are considered the gold standard. Unfortunately, their use has very serious limitations, given their high computational cost. In particular, the simulation of high-energy perturbations such as those involved in neutron or ion irradiation requires large simulation cells: a few hundred thousands of atoms at a minimum...

The effect of alloying nickel with iron on the supersonic ballistic stage of high energy displacement cascades

“…As evidenced in Refs. [19,21], these recoils lead to concerted motion of atoms. Low-density pockets of atoms are formed, surrounded by a high-density, supersonic pressure wave, involving pressures of the order of tens of GPa.…”

Slow relaxation of cascade-induced defects in Fe

“…In all cases, we see that the potential energy relaxation takes place over logarithmic timescales. For reference, we also performed SIA-cluster aggregation runs with the A04 po- tential; the results were similar to those with the M07 potential, as shown in the Supplemental Material [41]. The variation between each run for the SIA-clustering system is due to each simulation starting from a different random initial configuration.…”

“…4 quantifies this effect, which is in aggreement with visual inspection (see e.g. the movies in the Supplemental Material [41]). We identified the size and the center of mass (CoM) of each defect cluster at the end of each simulation and calculated the density of defects that were present in the neighborhood of the CoM in the local initial configuration, using gaussian kernel averaging.…”

“…Combined to the fact that potential energy relaxation takes place on a linear scale relative to the number of KMC steps (see Fig. 3 and the Supplemental Material [41]), this indicates that the largest barriers in each time-frame act as a bottleneck.…”

“…The variation between each run for the SIA-clustering system is due to each simulation starting from a different random initial configuration. In the Supplemental Material [41], we show that each of these runs is roughly logarithmic.…”