Kennedy, S.K., A.M. Dalley, and G.J. Kotyk, “Additive Manufacturing: Assessing Metal Powder Quality Through Characterizing Feedstock and Contaminants”, Journal of Materials Engineering and Performance, Vol. 28(2), pp. 728-740, 2019, DOI: 10.1007/s11665-018-3841-5.
The quality of powder feedstock for additive manufacturing (AM) metal powder bed fusion methods can significantly affect the quality of parts built from it. Particle size distribution (PSD) and shape factors influence flowability as well as the thickness and uniformity of each powder layer in the build box. For high-performance applications such as aerospace, medical, power generation and military, it becomes important to identify critical additional factors: the types, numbers and sizes of particulate contaminants that may be present in the powder. This is true for virgin, used and blended powders. Contaminants may be introduced during powder manufacture (e.g., ceramic insulation fragments from gas atomization equipment), handling (building insulation, talc) or possibly during the build process itself. Contaminants contained within a batch of powder can be physically built into an additive part when they are incorporated into the melt pool, and they can remain as discrete particulates or non-fused interfaces that act as stress concentrators. Their presence may decrease fatigue life by increasing the likelihood of fatigue crack initiation. This article describes three methods to rapidly and quantifiably characterize powder feedstock. (1) Computer-controlled scanning electron microscopy (CCSEM) provides quantitative size and shape parameters, as well as fine surface details from individual images on a particle-by-particle basis in large populations of powder. (2) Energy-dispersive spectroscopy (EDS) can be included, providing insights into variations within a batch of powder, as well as contaminant compositions. (3) For critical applications, the heavy liquid separation (HLS) method physically extracts low-density contaminants from a sample of powder metal down to part-per-billion detection limits to allow direct examination of contaminants and enhance identification and prevention of their sources. Altogether, these methods permit direct comparisons among powder metal samples. Better quantification of powder characteristics aids determination of suitability for end uses.
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