Materials & Design · 2018 · 81 citations · 53 references
EngineeringMaterials EngineeringMaterials ScienceAdditive ManufacturingMetallic MaterialsMetallurgyAlloysMetal Additive ManufacturingMetalsPhysical MetallurgySteel MaterialsWork HardeningAdditive Manufacturing AlloysLaser Metal DepositionMicrostructure CharacterizationSelective Laser MeltingStacking Fault EnergySteelsTensile TestingTransformation-induced Plasticity
High-manganese steels (HMnS) are alloys with outstanding mechanical properties, but their application is inhibited by inherent limitations in conventional processing. Additive manufacturing (AM) provides an alternative to make use of the unique properties of HMnS due to strongly differing processing conditions. However, no established methodology exists currently to tailor metallic alloys specifically for AM. Therefore, a methodology combining theoretical and experimental screening was used to design a HMnS specifically suited for AM. First, different chemical compositions were screened with thermodynamics-based stacking fault energy (SFE) maps to predict the activation of transformation-induced plasticity (TRIP) and twinning-induced plasticity (TWIP). For experimental screening, selected X30MnAl23-# alloys (with # ≤ 2 wt%) were produced by laser metal deposition (LMD). The metal physical mechanisms active during solidification and plastic deformation were identified by multiscale microstructure characterization (XRD, OM, SEM, EBSD, EDX, EPMA, APT) and tensile testing. Finally, two steels with the highest work-hardening capacity and formability were applied in lattice structures produced by selective laser melting (SLM) and compared to benchmark 316L steel. The correlation of AM-specific features of HMnS and their effect on deformation behavior as well as the applicability of the used methodology are discussed to illustrate the effectiveness of the chosen approach toward the development of high performance materials for AM.
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Additive manufacturing of metals
Dirk Herzog, Vanessa Seyda, Eric Wycisk et al. · Acta Materialia · 2016 · 4.6K citations · Full text
Engineering, Manufacturing Engineering, Materials Engineering +12
Texture Analysis with MTEX – Free and Open Source Software Toolbox
Florian Bachmann, Ralf Hielscher, Helmut Schaeben · Diffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena · 2010 · 2.7K citations
Natural Sciences, Materials Engineering, Materials Science +17