Simulation of precipitation in an aluminum scandium alloy using kinetic Monte Carlo and DBSCAN algorithms

Abstract

The present paper reports the precipitation process of Al3Sc structures in an aluminum scandium alloy, which has been simulated with a kinetic Monte Carlo (kMC) method. The kMC implementation is based on the vacancy diffusion mechanism. To filter the raw data generated by the kMC simulation, the density-based clustering with noise (DBSCAN) method was employed. kMC and DBSCAN algorithms were implemented in the C language. The undertaken simulations were conducted in the SeARCH cluster at the University of Minho. The study covers temperatures, concentrations, and dimensions, ranging from 578K to 873K, 0.25% to 5%, and 50x50x50 to 100x100x100. The Al3Sc precipitation was successfully simulated at the atomistic scale. DBSCAN revealed to be a valorous aid to identify the precipitates. The achieved results are in good agreement with those reported in the literature, but we went deeper in the evaluation of the influence of all the simulation and analysis parameters. A parallel version of the kMC algorithm using OpenMP was evaluated, which has not proved advantageous compared to the optimized sequential implementation.