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  1. Free, publicly-accessible full text available April 1, 2023
  2. Among metal additive manufacturing technologies, additive friction stir deposition stands out for its ability to create freeform and fully-dense structures without melting and solidification. Here, we employ a comparative approach to investigate the process-microstructure linkages in additive friction stir deposition, utilizing two materials with distinct thermomechanical behavior—an Al-Mg-Si alloy and Cu—both of which are challenging to print using beam-based additive processes. The deposited Al-Mg-Si is shown to exhibit a relatively homogeneous microstructure with extensive subgrain formation and a strong shear texture, whereas the deposited Cu is characterized by a wide distribution of grain sizes and a weaker shear texture. Wemore »show evidence that the microstructure in Al-Mg-Si primarily evolves by continuous dynamic recrystallization, including geometric dynamic recrystallization and progressive lattice rotation, while the heterogeneous microstructure of Cu results from discontinuous recrystallization during both deposition and cooling. In Al-Mg-Si, the continuous recrystallization progresses with an increase of the applied strain, which correlates with the ratio between the tool rotation rate and travel velocity. Conversely, the microstructure evolution in Cu is found to be less dependent on , instead varying more with changes to . This difference originates from the absence of Cu rotation in the deposition zone, which reduces the influence of tool rotation on strain development. We attribute the distinct process-microstructure linkages and the underlying mechanisms between Al-Mg-Si and Cu to their differences in intrinsic thermomechanical properties and interactions with the tool head.« less
  3. Metal additive manufacturing (AM) provides a platform for microstructure optimization via process control, but establishing a quantitative processing-microstructure linkage necessitates an efficient scheme for microstructure representation and regeneration. Here, we present a deep learning framework to quantitatively analyze the microstructural variations of metals fabricated by AM under different processing conditions. The principal microstructural descriptors are extracted directly from the electron backscatter diffraction patterns, enabling a quantitative measure of the microstructure differences in a reduced representation domain. We also demonstrate the capability of predicting new microstructures within the representation domain using a regeneration neural network, from which we are able tomore »explore the physical insights into the implicitly expressed microstructure descriptors by mapping the regenerated microstructures as a function of principal component values. We validate the effectiveness of the framework using samples fabricated by a solid-state AM technology, additive friction stir deposition, which typically results in equiaxed microstructures.« less
  4. Additive friction stir deposition is an emerging solid-state additive manufacturing technology that enables site-specific build-up of high-quality metals with fine, equiaxed microstructures and excellent mechanical properties. By incorporating proper machining, it has the potential to produce large-scale, complex 3D geometries. Still early in its development, a thorough understanding of the thermal process fundamentals, including temperature evolution and heat generation mechanisms, has not been established. Here, we aim to bridge this gap through in situmonitoring of the thermal field and material flow behavior using complementary infrared imaging, thermocouple measurement, and optical imaging. Two materials challenging to print via beam-based additive technologies,more »Cu and Al-Mg-Si, are investigated. During additive friction stir deposition of both materials, we find similar trends of thermal features (e.g., the trends of peak temperature , exposure time, and cooling rate) with respect to the processing conditions (e.g., the tool rotation rate and in-plane velocity ). However, there is a salient, quantitative difference between Cu and Al-Mg-Si; exhibits a power law relationship with / in Cu but with / in Al-Mg-Si. We correlate this difference to the distinct interfacial contact states that are observed through in situ material flow characterization. In Cu, the interfacial contact between the material and tool head is characterized by a full slipping condition, so interfacial friction is the dominant heat generation mechanism. In Al-Mg-Si, the interfacial contact is characterized by a partial slipping/sticking condition, so both interfacial friction and plastic energy dissipation contribute significantly to the heat generation.« less