journal article·2024-01Open access

Triple junction disclinations in severely deformed Cu–0.4%Mg alloys

Siying Zhu, Andrey P. Jivkov, Elijah Borodin, Anna Bodyakova

Acta Materialia· Volume 264

Abstract

Stress fields arising from triple junction disclinations (TJDs) play a significant role in the microstructure evolution during the plastic deformation of metals. The calculation of TJD strengths from grain orientation data was developed by Bollmann more than 50 years ago, but so far applied only to collections of a few grains. Developed here is a new methodology for calculating TJD strengths and the associated stress fields in large polycrystalline assemblies using experimental electron back-scattered diffraction (EBSD) maps. The methodology combines Bollmann’s approach with a representation of materials as cell complexes. It is computationally efficient and allows for obtaining the spatial distribution of TJD strengths from EBSD images containing thousands of grains. Analysed are the fraction, distribution, and strengths of TJDs within statistically representative microstructures of Cu-0.4%Mg alloy subjected to severe plastic deformation (SPD) by equal channel angular pressing. It is shown that the formation of low-angle grain boundaries (dislocation walls) during SPD leads to an increasing number of TJDs, whose spatial distribution is progressively more uniform and whose strength distribution remains nearly constant. This result suggests that the SPD reduces the internal stresses associated with disclinations in large regions of the material, as closely situated disclinations screen each other’s fields. Regions with high local stresses can be expected between sparsely distributed TJDs with the highest strengths. The average distance between such TJDs could be considered as a natural length scale in a material.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Microstructure and mechanical properties · Aluminum Alloy Microstructure Properties · Metal Forming Simulation Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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