The Influence of atmospheric oxygen content on the mechanical properties of selectively laser melted AlSi10Mg TPMS-based lattice
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AbstractSelective Laser Melting (SLM) is an emerging Additive Manufacturing (AM) technique for the on-demand fabrication of metal parts. The mechanical properties of Selectively Laser Melted (SLMed) parts are sensitive to oxygen concentration within the SLM build chamber due to the formation of oxides, which may lead to various negative consequences. As such, this work explores the influence of SLM atmospheric Oxygen Content (OC) on the macroscopic mechanical properties of SLMed AlSi10Mg bulk material and Triply Periodic Minimal Surface (TPMS) lattices namely primitive, gyroid, and diamond. Standard quasi-static tensile and crushing tests were conducted to evaluate the bulk properties of AlSi10Mg and the compressive metrics of TPMS-lattices. Two oxygen concentrations of 100 ppm and 1000 were used during the SLM fabrication of the experimental specimens. The tensile test data revealed a small influence of the oxygen content on the bulk properties. The low oxygen concentration improved the elongation while slightly reduced the ultimate tensile strength and yield stress. Similarly, the influence of the oxygen content on the compressive responses of TPMS-lattices was generally limited and primarily depended on their geometrical configuration. This study elucidates the role of SLM atmospheric oxygen content on the macroscopic behaviour of SLMed AlSi10Mg parts.
CitationBaroutaji A, Arjunan A, Beal J, Robinson J, Coroado J. (2023) The Influence of Atmospheric Oxygen Content on the Mechanical Properties of Selectively Laser Melted AlSi10Mg TPMS-Based Lattice. Materials, 16(1):430. https://doi.org/10.3390/ma16010430
Description© 2023 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/ma16010430
SponsorsThis research was conducted with support from Innovate UK Knowledge Transfer Partnership KTP013117 (University of Wolverhampton/AceOn), AceOn Group Ltd., the University of Wolverhampton, Linde Group, Additive Analytics Ltd. and EOS GmbH.
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0/