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A comprehensive approach to powder feedstock characterization for powder bed fusion additive manufacturing: a case study on AlSi7Mg

Jose Alberto Muniz-Lerma (1), Amy Nommeots-Nomm (1), Kristian Edmund Waters (2), and Mathieu Brochu (1)

Materials, 11(12), 2386, 27 November 2018. DOI: 10.3390/ma11122386

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Keywords

Additive manufacturing; Metal powders; Powder flowability; Aluminium; AlSi7Mg; Powder properties; Water absorption

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Abstract

In powder bed fusion additive manufacturing, the powder feedstock quality is of paramount importance; as the process relies on thin layers of powder being spread and selectively melted to manufacture 3D metallic components. Conventional powder quality assessments for additive manufacturing are limited to particle morphology, particle size distribution, apparent density and flowability. However, recent studies are highlighting that these techniques may not be the most appropriate. The problem is exacerbated when studying aluminium powders as their complex cohesive behaviors dictate their flowability. The current study compares the properties of three different AlSi7Mg powders, and aims to obtain insights about the minimum required properties for acceptable powder feedstock. In addition to conventional powder characterization assessments, the powder spread density, moisture sorption, surface energy, work of cohesion, and powder rheology, were studied. This work has shown that the presence of fine particles intensifies the pick-up of moisture increasing the total particle surface energy as well as the inter-particle cohesion. This effect hinders powder flow and hence, the spreading of uniform layers needed for optimum printing. When spherical particles larger than 48 µm with a narrow particle distribution are present, the moisture sorption as well as the surface energy and cohesion characteristics are decreased enhancing powder spreadability. This result suggest that by manipulating particle distribution, size and morphology, challenging powder feedstock such as Al, can be optimized for powder bed fusion additive manufacturing…

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How Our Software Was Used

Image visualization and reconstruction.

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Author Affiliation

(1) REGAL Aluminum Research Center, Department of Mining and Materials Engineering, McGill University, Montreal, QC H3A 0C5, Canada
(2) Department of Mining and Materials Engineering, McGill University, Montreal, QC H3A 0C5, Canada

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