Quantification of Slip Band Distribution in Polycrystals: An Automated Fast Fourier Transform Decomposition Approach

Abstract

AbstractPlastic deformation is accumulated in slip bands in a wide variety of engineering alloys. Multiple material and loading conditions impact their distribution and degree of slip localization, but these effects are rarely quantified. To tackle this, the current work introduces a fast Fourier transform (FFT) decomposition method and applies it to a tensile-loaded polycrystalline nickel-based superalloy imaged via high-resolution digital image correlation and electron backscatter diffraction. This approach identifies active slip planes over the FFT images of individual grains and performs inverse transforms such that slip band traces with shared orientations are isolated. This technique enabled the largest quantification of slip band spacings and in-plane strains to date, with a total of 6,557 slip bands detected. The results show that the slip band spacings increase with grain size, with no evident dependence on grain orientation and Schmid factor. Slip bands are found to develop similar spacings along different octahedral planes and continue to spread over larger regions of the grain as the resolved shear stress of the active slip system increases. The FFT decomposition technique, which could be employed with multiple microscopy techniques, will allow for much-needed large-scale quantitative studies of slip localization.