Dataset: Quantifying the fingerprint of twinned microstructures through surface and three-dimensional techniques: a comparative study

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Published: 1 month ago Views: 33 Downloads: 3 DOI: 10.13011/m3-66pj-k548 License: Attribution License (ODC-By) Size: 14.46 GB
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  • Duncan Greeley
  • Hi Vo
  • Rodney McCabe
  • Matthew Schneider
  • Carlos Tome
  • Laurent Capolungo

Assessing the fingerprint of a material’s microstructure is key for supporting materials design. With the emergence of a wide range of 3D characterization techniques, it is critical to understand the main differences in fingerprints reconstructed from 2D and 3D datasets. To this end, we introduce a graph-based microstructure reconstruction framework that enables structural comparisons of twin domain networks in high purity Ti using 3D and 2D electron backscatter diffraction. Insights into the structure of the twin networks are facilitated by combining statistical analysis of twin crystallography with visual and graphical analysis of the novel graph abstractions of the twins. We demonstrate that compared to 3D reconstructions, conventional 2D views of twinning miss key aspects of the microstructure including the high interconnectivity of domains into networks that span the full reconstruction volume. The reduced cross-grain and in-grain twin connectivity typically observed in 2D has notable implications on our understanding of how twinning mediates the plastic response of microstructures and how twin networks evolve. It is thus clear that 3D characterization is critical for accurately inferring both twin network morphologies as well as the key unit processes facilitating network formation.

This work was fully funded by the US. Department of Energy, Office Basic Energy Sciences Project FWP 06SCPE401. The 3D data was obtained at the Electron Microscopy Laboratory at Los Alamos and Los Alamos National Laboratory, an affirmative action equal opportunity employer, is managed by Triad National Security, LLC for the U.S. Department of Energy's NNSA, under contract 89233218CNA000001.

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