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The current study utilized a two-step laser power bed fusion (LPBF) method to create a heterostructured material (HSM) composed of STS316L and Inconel 718. STS316L enhances ductility, while Inconel 718 improves strength. We examined the tensile deformation behavior of HSMs and found that stress is mainly localized in the cell or grain boundary area. The volumetric ratio of Inconel 718 to STS316L in the HSM affects the tensile properties, although the structural design is crucial for improving tensile strength. Fractographic analysis revealed that fracture occurred and propagated at the STS316L and Inconel 718 interface, with evident unmelted powders due to insufficient energy density. Achieving an optimized process parameter is necessary to ensure a reliable chemical joining which increases the mechanical properties of HSM. [ABSTRACT FROM AUTHOR]

The core challenge in directed energy deposition is to obtain high surface quality through process optimisation, which directly affects the mechanical properties of fabricated parts. However, for expensive materials like Ti-6Al-4V, the cost and time required to optimise process parameters can be excessive in inducing good surface quality. To mitigate these challenges, we propose a novel method with artificial intelligence to generate virtual surface morphology of Ti-6Al-4V parts by given process parameters. A high-resolution surface morphology image generation system has been developed by optimising conditional generative adversarial networks. The developed virtual surface matches experimental cases well with an Fréchet inception distance score of 174, in the range of accurate matching. Microstructural analysis with parts fabricated with artificial intelligence guidance exhibited less textured microstructural behaviour on the surface which reduces the anisotropy in the columnar structure. This artificial intelligence guidance of virtual surface morphology can help to obtain high-quality parts cost-effectively. [ABSTRACT FROM AUTHOR]