Interface evolution behaviors and shear strength of vacuum diffusion bonded 45 steel/additive manufactured 316L stainless steel joints
Source abstract
Abstract
The combination of austenitic stainless steel and carbon steel can combine the advantages of both materials, offering superior corrosion resistance and environmental stability, while also providing high strength and good machinability. In this study, casting 45 steel and additive manufactured 316 L stainless steel were diffusion bonded at 900 °C under a pressure of 15 MPa in a vacuum environment for bonding time of 5, 20, 40, and 60 min. The interface behaviors, including void closure, interface grain boundary (IGB) migration, element diffusion and the development of interfacial layers were obtained and analyzed in detail. The interface transition zone from the 316 L stainless steel to the 45 steel consists of the metallic elements diffusion layer and the carbide layer. During the bonding process, the original bonding interface transformed into interface grain boundary (IGB) and IGB migrations occurred at the triple junction structures only from the 316 L stainless steel to the 45 steel under the effect of element concentration gradient. The interfacial voids would not move with the interface migrations but form a void residual layer and some small diffusion voids caused by the Kirkendall effect appear on the 316 L stainless steel. As the bonding time increases, interfacial voids transform from large irregular shapes to small rounded shapes due to plastic deformation and surface diffusion. The shear strength of the joints initially increases due to void closure and IGB migrations, reaching a maximum of 487 MPa at 40 min, but then decreases due to the large amount of carbides generated at 60 min leading to brittle fracture.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Additive Manufacturing Materials and Processes · High Entropy Alloys Studies · Intermetallics and Advanced Alloy Properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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