SLIDE: Automated Identification and Quantification of Grain Boundary Sliding and Opening in 3D

Abstract

Grain Boundary (GB) deformation mechanisms such as Sliding (GBS) and Opening (GBO) are prevalent in alloys at high homologous temperatures but are hard to capture quantitatively. We propose an automated procedure to quantify 3D GB deformations at the nanoscale, using a combination of precisely aligned Digital Image Correlation (DIC), electron backscatter diffraction, optical profilometry, and in-beam secondary electron maps. The framework, named Sliding identification by Local Integration of Displacements across Edges (SLIDE), (i) distinguishes GBS from GBO, (ii) computes the datapoint-wise measured in-plane displacement gradient tensor (from DIC), (iii) projects this data onto the theoretical GBS tensor to reject near-GB plasticity/elasticity/noise, and (iv) adds the out-of-plane step from optical profilometry to yield the local 3D GBS/GBO vector; automatically repeated for each $\sim$50nm-long GB segment. SLIDE is validated on a virtual experiment of discrete 3D sliding, and successfully applied to Zn-coated steel experiments, yielding quantitative GBS/GBO activity maps.

accepted for publication in Scripta Materialia

References in corpus (3)

• Automated Identification of Slip System Activity Fields from Digital Image Correlation Data
• Martensite plasticity and damage competition in dual-phase steel: A micromechanical experimental-numerical study
• +SSLIP: Automated Radon-Assisted and Rotation-Corrected Identification of Complex HCP Slip System Activity Fields from DIC Data