Dislocation dynamics in Ni: Parameterizing dislocation trajectories from atomistic simulations

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We present a methodology using Differential Evolution Monte Carlo (DE-MC) to fit the parameters of an equation of motion to molecular dynamics (MD) trajectories of an a2〈110〉{111} edge dislocation in pure face-centered cubic (FCC) Ni, which is used as a model system. The motion of the edge dislocation under shear was observed using MD simulations with a classical effective potential, and the dislocation position was extracted. The parameters of interest were the effective mass, drag coefficient, and force experienced by the dislocation. Using DE-MC within a Bayesian framework, we estimated the joint posterior distribution of the parameters from the accepted samples produced by the DE-MC algorithm. The obtained distribution was then used to propagate the parameter uncertainties through the model, the equation of motion, which was used to predict the dislocation positions and velocities at the simulation timesteps as well as the uncertainty in the predictions. The mean fit was found to match the MD dislocation position data with a root mean square error (RMSE) of 0.2nm. We demonstrate how parameter distributions determined using the proposed methodology can be applied to obtain a mobility law for the class of dislocations studied with quantified uncertainties. This work is part of a longer-term study aiming to develop a surrogate model for precipitation strengthening, specifically dislocation-precipitate interactions, in Ni-based superalloys with uncertainty quantification. Accordingly, we also discuss the limitations of the selected model within this context and the necessary model extensions to overcome them. Published by the American Physical Society 2024