Correlation of Grain Statistics with various Properties on Industrial Alloys
Fig. 1.1: Pattern Quality Map depicting the microstructure of a Ni-alloy sample with a bimodal distribution of grain sizes; map was acquired using eFlash XS EBSD detector mounted on JSM IT200 SEM
One of the most important benefits of EBSD technique is the output of reliable grain statistics; for example average diameter size and distribution. This can be correlated with various properties of the analyzed material, hardness, strength and plasticity/formability. ESPRIT 2 software detects grains using misorientation and size criteria and calculates automatically the mean equivalent diameter size using area weighted and arithmetic mean methods. Grain size and shape statistics are complemented by a multitude of subsetting options to create powerful microstructure quantification tools which support scientists and engineers in the process of understanding and/or predicting materials properties.
Fig. 1.2: Crystal orientation map of the Ni-alloy sample, displaying the orientation of each grain by relating the color code described in the upper left corner with the sample surface normal; acquisition speed: 510frames/sec, zero solutions: 1.3%. No data cleaning applied!
Fig. 1.3: Subset of the Ni-alloy EBSD map showing in random colors all grains with an equivalent diameter larger than 70microns; 1% of the total number of grains represent ~42% of the map area
Fig. 1.4: Subset of the Ni-alloy EBSD map showing in random colors all grains with an equivalent diameter smaller than 70microns; there are 2250 grains representing ~58% of the map area
Fig. 1.5a: Grain size distribution histogram and mean grain diameter size calculated using arithmetic mean; the median value for grain diameter size is also calculated & displayed automatically as well as the total number of grains considered in statistics
Fig. 1.5b: Grain size distribution histogram and mean grain diameter size calculated using area weighting, i.e. larger grains have a bigger influence on the mean diameter size value. For materials with a bimodal distribution of grain sizes, using area weighting is recommended when trying to correlate the mean grain diameter size value with mechanical properties, e.g. strength, stiffness, hardness, etc.