A comparison of particle size distribution and morphology data acquired using lab-based and commercially available techniques: Application to stainless steel powder

The particle size distribution (PSD) and particle morphology of metal powders undoubtedly affects the quality of parts produced by additive manufacturing (AM). It is, therefore, crucial to accurately know the PSD and morphology of these powders. There exist several measurement techniques for these quantities, but since each method is based on different physical phenomena, which are sensitive to different aspects of a particle's shape and size, it is unclear how the measured PSDs and morphology compare to one another. In this study, five different techniques are used: sieve analysis, dynamic imaging analysis, laser diffraction analysis, X-ray computed tomography (XCT), and scanning electron microscopy. The first three are commonly used in the powder metallurgy field while the last two are laboratory-based tools capable of providing robust size and shape data. Nominally identical samples of stainless-steel powders were produced via riffling, and each technique was employed to measure effectively the same PSD and in some cases the morphology. In this paper, the differences among these measurement techniques are explored by a comparison of the measured results. Besides the random variations of the various measurement processes, the difference in the results is partly due to the fact that the particles are not perfectly spherical and that there are many multi-particles present. Each of these affect the principle of each method differently. Three-dimensional particle morphology and size data collected via XCT is used to provide insight regarding the discrepancies among other sizing and morphology measurement techniques. (Official contribution of the National Institute of Standards and Technology; not subject to copyright in the United States.)

Automated summary

The particle size distribution and morphology of metal powders play a crucial role in the quality of 3D printed parts. Accurate understanding of these parameters is important. This study compares different measurement techniques and provides insight into the discrepancies among them using XCT data.