Plastic deformation behaviour of layer-grained silver polycrystalline from atomistic simulation

Abstract

Two types of nanocrystalline polycrystalline silver models in bulk, film and nanowire forms were constructed with layer-grained or equiaxed grain morphologies and average grain sizes of ~7.8 and ~14.7 nm. Uniaxial tensile deformation was performed to investigate the effect of grain morphology and free surface on the plastic deformation behaviour under the strain rate of 5 × 10⁸ and 10⁷ s⁻¹ at 0.1 K. Grain Boundary (GB) orientation and dimensions in layer-grained morphology promoted the formation of sessile dislocation structures. Some dislocations interacted with each other and some dislocations got obstructed by stacking faults. However, the resulting configurations did not last long enough to cause strain hardening. Strain softening was observed in all models except for the layer-grained models in bulk form, where steady plastic flow was observed after yield. The location and orientation of free surfaces with respect to GBs imposed geometric constraints on the deformation mechanisms (GB sliding and formation of sessile dislocations) which produced asymmetric stress states that influenced the elastic as well as plastic response of the material. The yield stress and flow stress were much smaller at lower strain rate simulations. The proportion of perfect dislocations increased as the strain rate decreased from 5 × 10⁸  to 10⁷ s⁻¹ due to the decrease of applied stress. Dislocations were mainly emitted from grain boundaries or triple junctions at both high and low strain rate deformations. These results provided insights into the understanding of layer-grained nanocrystalline materials and the synthesis of materials with both high strength and ductility.

Keyword:

• Plastic deformation
• layer-grained morphology
• tension
• polycrystalline metals
• atomistic simulation

Acknowledgements

The authors gratefully acknowledge the support from the National Natural Science Foundation of China. The authors acknowledge computational resource grant #PAS0187 from the Ohio Super Computer Center, USA.