Predictive machine learning approaches for the microstructural behavior of multiphase zirconium alloys.

Zirconium alloys are widely used in harsh environments characterized by high temperatures, corrosivity, and radiation exposure. These alloys, which have a hexagonal closed packed (h.c.

Data-driven analysis of neutron diffraction line profiles: application to plastically deformed Ta.

Non-destructive evaluation of plastically deformed metals, particularly diffraction line profile analysis (DLPA), is valuable both to estimate dislocation densities and arrangements and to validate microstructure-aware constitutive models. To date, the interpretation of whole line diffraction profiles relies on the use of semi-analytical models such as the extended convolutional multiple whole profile (eCMWP) method. This study introduces and validates two data-driven DLPA models to extract dislocation densities from experimentally gathered whole line diffraction profiles.

Characteristic boundaries associated with three-dimensional twins in hexagonal metals.

Twinning is a critically important deformation mode in hexagonal close-packed metals. Twins are three-dimensional (3D) domains, whose growth is mediated by the motion of facets bounding the 3D twin domains and influences work hardening in metals. An understanding of twin transformations therefore necessitates that the atomic-scale structure and intrinsic mobilities of facets be known and characterized.