Atomistic multiscale simulations on the anisotropic tensile behaviour of copper-alloyed alpha-iron at different states of thermal ageing

Abstract

The mechanical behaviour of steels is strongly related to their underlying atomistic structures which evolve during thermal treatment. Cu-alloyed α-Fe undergoes a change in material behaviour during the ageing process, especially at temperatures of above 300°C, where precipitates form on a large time-scale within the α-Fe matrix, yielding first a precipitation strengthening of the material. As the precipitates grow further in time, the material strength decreases again. This complex process is modelled with a multiscale approach, combining Kinetic Monte Carlo (KMC) with Molecular Dynamics (MD) simulations in a sequential way and exploiting the advantages of both methods while simultaneously circumventing their particular disadvantages. The formation of precipitates is modelled on a single-crystal lattice with a diffusion based KMC approach. Transferring selected precipitation states at different ageing times to MD simulations allows the performance of nano tensile tests and the analysis of failure initiation. The anisotropic tensile behaviour is investigated in the [100], [110] and [111] directions, showing monotonically decreasing tensile strengths and deformation strains. Hence precipitation strengthening is mainly due to dislocation–precipitate interactions which are non-existent at small tensile loadings in this scenario. At the point of ductile failure, dislocations are generated at the interfaces between precipitates and the Fe matrix. Straining in the [100] direction, they lie on {110} and {112} glide planes, as expected. With the method presented here, the changes of the anisotropic tensile moduli are related to different states of thermal ageing, i.e., to nucleation, growth and Ostwald ripening of Cu precipitates.

Keywords:

• multiscale
• Kinetic Monte Carlo
• Molecular Dynamics
• precipitation
• ferritic alloy
• nano tensile test
• sequential coupling

Acknowledgements

D. Molnar and S. Schmauder would like to thank the German Research Foundation (DFG) for financial support of the project within the Cluster of Excellence in Simulation Technology (EXC 310/1) at the University of Stuttgart. P. Binkele and S. Schmauder would like to thank the German Research Foundation (DFG) for financial support of the project SCHM746/71-2.