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Reduction of oxygen content in laser powder bed fusion process atmosphere - Effects on stochastic defect formation and mechanical properties
Chalmers Univ Technol, Sweden.
Linköping University, Department of Management and Engineering, Engineering Materials. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-8304-0221
Fed Inst Metrol METAS, Switzerland.
Fed Inst Metrol METAS, Switzerland.
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2024 (English)In: Journal of Materials Research and Technology, ISSN 2238-7854, E-ISSN 2214-0697, Vol. 30, p. 4667-4681Article in journal (Refereed) Published
Abstract [en]

Stochastic defects in materials manufactured via laser powder bed fusion (LPBF) can severely compromise mechanical performance and are challenging to predict and detect, thus motivating the development of defect mitigation strategies. Particle oxidation is a factor well-known to generate defects by disturbing melt pool dynamics. If the particles are spatters, additional disturbances increase the likelihood of defect formation. In this study, restricting oxygen content in the process atmosphere to 50 ppm is investigated to minimize stochastic spatter-induced defects and improve the mechanical properties of Hastelloy X. Specimens were manufactured under this condition at two nominal layer thicknesses, analyzed for internal defects, and mechanically tested. Contrary to expectations, reducing the oxygen content did not prevent spatter-induced defect formation; rather, it could exacerbate the formation of more numerous and larger defects. Nevertheless, this tighter control of the process atmosphere led to significant microstructural refinement, which, when combined with sparse defects, resulted in improved fatigue performance. Despite the inherent ductility of Hastelloy X, the presence of abundant defects significantly larger than the microstructural characteristic size proved detrimental to fatigue performance. Notably, the occurrence of defects exhibited considerable variation across the build area, contributing to scatter in fatigue data. However, quantitative analysis of in-situ monitoring data enabled prediction of variability in defect content and mechanical performance.

Place, publisher, year, edition, pages
ELSEVIER , 2024. Vol. 30, p. 4667-4681
Keywords [en]
In-situ monitoring; Defect detection; Defect mitigation; Oxidation; Spatter; Fatigue
National Category
Other Materials Engineering
Identifiers
URN: urn:nbn:se:liu:diva-204354DOI: 10.1016/j.jmrt.2024.04.177ISI: 001236837200001OAI: oai:DiVA.org:liu-204354DiVA, id: diva2:1868714
Note

Funding Agencies|Vinnova [2022-02549]; European Union [820774]; Competence Centre for Additive Manufacturing - Metal (CAM2); Production Area of Advance at Chalmers and LIGHTer Academy

Available from: 2024-06-12 Created: 2024-06-12 Last updated: 2024-09-02

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  • apa
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