Proliferation of twinning in hexagonal close-packed metals: Application to magnesium
Plastic deformation of metallic alloys usually takes place through slip, but occasionally involves twinning. In particular, twinning is important in hexagonal close packed (HCP) materials where the easy slip systems are insufficient to accommodate arbitrary deformations. While deformation by slip mechanisms is reasonably well understood, comparatively less is known about deformation by twinning. Indeed, the identification of relevant twinning modes remains an art. In this paper, we develop a framework combining a fundamental kinematic definition of twins with large-scale atomistic calculations to predict twinning modes of crystalline materials. We apply this framework to magnesium where there are two accepted twin modes, tension and compression, but a number of anomalous observations. Remarkably, our framework shows that there is a very large number of twinning modes that are important in magnesium. Thus, in contrast to the traditional view that plastic deformation is kinematically partitioned between a few modes, our results suggest that deformation in HCP materials is the result of an energetic and kinetic competition between numerous possibilities. Consequently, our findings suggest that the commonly used models of deformation need to be extended in order to take into account a broader and richer variety of twin modes, which, in turn, opens up new avenues for improving the mechanical properties.
© 2017 Elsevier Ltd. Received 3 August 2017, Revised 8 December 2017, Accepted 19 December 2017, Available online 21 December 2017. This work draws from the doctoral thesis of DS at the California Institute of Technology, and was initiated when MP also held a position there. Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-12-2-0022 and also through the National Defense Science and Engineering Graduate Fellowship. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwith- standing any copyright notation herein. We gratefully acknowledge the support from the Natural Sciences and Engineering Research Council of Canada (NSERC) through the Discovery Grant under Award Application Number RGPIN-2016-06114 and the support of Compute Canada through the Westgrid consortium for giving access to the supercomputer grid. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.
Submitted - 1708.01662.pdf