ArticleMicromachines2021
A Layer-Dependent Analytical Model for Printability Assessment of Additive Manufacturing Copper/Steel Multi-Material Components by Directed Energy Deposition.
Article in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Influence of Powder Type and Layer-Dependent Energy Input on Multi-Layer Laser Cladding of Ductile Cast Iron.Micromachines · 2026Article
- High-Performance Advanced Composites in Multifunctional Material Design: State of the Art, Challenges, and Future Directions.Materials (Basel, Switzerland) · 2024Review
- Editorial for the Special Issue on Laser Additive Manufacturing: Design, Processes, Materials and Applications.Micromachines · 2022Article
- Laser Additive Manufacturing of Anti-Tetrachiral Endovascular Stents with Negative Poisson's Ratio and Favorable Cytocompatibility.Micromachines · 2022Article
- A Review on Macroscopic and Microstructural Features of Metallic Coating Created by Pulsed Laser Material Deposition.Micromachines · 2022Review
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Authors and funding
6 authors.
Funding
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Abstract
Copper/steel bimetal, one of the most popular and typical multi-material components (MMC), processes excellent comprehensive properties with the high strength of steel and the high thermal conductivity of copper alloy. Additive manufacturing (AM) technology is characterized by layer-wise fabrication, and thus is especially suitable for fabricating MMC. However, considering both the great difference in thermophysical properties between copper and steel and the layer-based fabrication character of the AM process, the optimal processing parameters will vary throughout the deposition process. In this paper, we propose an analytical calculation model to predict the layer-dependent processing parameters when fabricating the 07Cr15Ni5 steel on the CuCr substrate at the fixed layer thickness (0.3 mm) and hatching space (0.3 mm). Specifically, the changes in effective thermal conductivity and specific heat capacity with the layer number, as well as the absorption rate and catchment efficiency with the processing parameters are considered. The parameter maps predicted by the model have good agreement with the experimental results. The proposed analytical model provides new guidance to determine the processing windows for novel multi-material components, especially for the multi-materials whose physical properties are significantly different.
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