Long Timothy J H, Holbrook William, Hufnagel Todd C, Mueller Tim
Hopkins Extreme Materials Institute, Johns Hopkins University, Baltimore, Maryland, USA.
Department of Materials Science and Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
J Microsc. 2024 Jan;293(1):20-37. doi: 10.1111/jmi.13247. Epub 2023 Dec 18.
Because microstructure plays an important role in the mechanical properties of structural materials, developing the capability to quantify microstructures rapidly is important to enabling high-throughput screening of structural materials. Electron backscatter diffraction (EBSD) is a common method for studying microstructures and extracting information such as grain size distributions (GSDs), but is not particularly fast and thus could be a bottleneck in high-throughput systems. One approach to accelerating EBSD is to reduce the number of points that must be scanned. In this work, we describe an iterative method for reducing the number of scan points needed to measure GSDs using incremental low-discrepancy sampling, including on-the-fly grain size calculations and a convergence test for the resulting GSD based on the Kolmogorov-Smirnov test. We demonstrate this method on five real EBSD maps collected from magnesium AZ31B specimens and compare the effectiveness of sampling according to two different low discrepancy sequences, the Sobol and R sequences, and random sampling. We find that R sampling is able to produce GSDs that are statistically very similar to the GSDs of the full density grids using, on average, only 52% of the total scan points. For EBSD maps that contained monodisperse GSDs and over 1000 grains, R sampling only required an average of 39% of the total EBSD points.
