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Corrosion-Fatigue Performance of 3D-Printed (L-PBF) AlSi10Mg
RISE Research Institutes of Sweden, Materials and Production, Corrosion.ORCID iD: 0000-0003-0611-3324
RISE Research Institutes of Sweden, Materials and Production, Corrosion.ORCID iD: 0000-0002-6847-5446
RISE Research Institutes of Sweden, Materials and Production, Manufacturing Processes.ORCID iD: 0000-0002-9411-3756
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2023 (English)In: MATERIALS, Vol. 16, no 17, article id 5964Article in journal (Refereed) Published
Abstract [en]

Additive manufacturing (AM) allows for optimized part design, reducing weight compared to conventional manufacturing. However, the microstructure, surface state, distribution, and size of internal defects (e.g., porosities) are very closely related to the AM fabrication process and post-treatment operations. All these parameters can have a strong impact on the corrosion and fatigue performance of the final component. Thus, the fatigue-corrosion behavior of the 3D-printed (L-PBF) AlSi10Mg aluminum alloy has been investigated. The influence of load sequence (sequential vs. combined) was explored using Wohler diagrams. Surface roughness and defects in AM materials were examined, and surface treatment was applied to improve surface quality. The machined specimens showed the highest fatigue properties regardless of load sequence by improving both the roughness and removing the contour layer containing the highest density of defect. The impact of corrosion was more pronounced for as-printed specimens as slightly deeper pits were formed, which lowered the fatigue-corrosion life. As discussed, the corrosion, fatigue and fatigue-corrosion mechanisms were strongly related to the local microstructure and existing defects in the AM sample.

Place, publisher, year, edition, pages
MDPI , 2023. Vol. 16, no 17, article id 5964
Keywords [en]
atmospheric corrosion; fatigue; additive manufacturing; 3D printing; aluminum alloys; AlSi10Mg
National Category
Materials Engineering
Identifiers
URN: urn:nbn:se:ri:diva-70148DOI: 10.3390/ma16175964OAI: oai:DiVA.org:ri-70148DiVA, id: diva2:1830206
Note

This research received no external funding.

Available from: 2024-01-22 Created: 2024-01-22 Last updated: 2024-05-21Bibliographically approved

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Linder, ClaraVucko, FlavienMa, TaoranProper, SebastianDartfeldt, Erik

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