Laser-based Directed Energy Deposition (DED-LB) enables the fabrication of multi-material and compositionally graded metallic components. Yet, ensuring accurate local composition during printing remains a major challenge, especially critical for systems with strongly dissimilar physical and thermo-physical properties. In this study, a hyperspectral in-situ monitoring approach is proposed to detect and quantify compositional variations during the DED-LB fabrication of 316L to CuCr1Zr multi-material structures. Hyperspectral imaging captures the spatially resolved spectral emission of the melt pool, providing a high-dimensional representation of its thermal and radiative state that is sensitive to changes in material composition. A data-driven model based on Convolutional Neural Networks (CNN) is trained to correlate hyperspectral signatures with the local compositional ratio under varying processing conditions, enabling real-time classification of compositional states during deposition. The proposed method demonstrates high accuracy in identifying compositional transitions and detecting deviations from the designed gradient, even in the presence of melt pool instabilities inherent to the Fe–Cu system. Post-process characterization confirms a strong agreement between hyperspectral predictions and measured elemental composition. These results highlight the potential of hyperspectral in-situ monitoring and CNN classification as a powerful tool for real-time composition sensing and closed-loop control in multi-material DED-LB, paving the way toward more reliable fabrication of functionally graded metallic components.
Electron backscatter diffraction (EBSD) is widely used in the additive manufacturing (AM) community to characterize dislocation density, but the validity of EBSD-based misorientation metrics for quantitatively estimating plastic strain and dislocation structures in AM materials has not been comprehensively established. This study evaluates average intragranular misorientation (AIM), grain orientation spread (GOS), kernel average misorientation (KAM), and geometrically necessary dislocation (GND) density for plastic strain quantification in laser powder directed energy deposited (LP-DED) 316H stainless steel. Wrought 316H subjected to controlled tensile deformation up to 30% plastic strain established calibration curves relating plastic strain, Vickers hardness, and each EBSD metric. Independent cross-validation was performed via TEM-measured dislocation density. KAM and GND density were found to track the same lattice curvature content. Step-size sensitivity analysis showed that AIM is effectively independent of EBSD step size while KAM scales nearly linearly at 0.058 ± 0.012°/µm. EBSD performed at a small step size determined that the dislocation cell wall misorientation (~0.06 to 0.1°) observed in AM materials falls below the standard EBSD noise floor (~0.2°), indicating that cellular structure domain boundaries and low-angle boundaries are the primary source of the KAM signal in the materials studied in this work. Monte Carlo resampling large-area scans (8.4 ×3 mm2, 2,500-5,000+ grains) demonstrated that KAM converges within 85 to 145 grains, roughly one order of magnitude fewer than the 2,200 to 3,650 grains required for AIM. AIM exhibited an increase after solution annealing, attributed to retained low-angle boundaries after partial recrystallization, while KAM correctly tracked the reduction in dislocation density confirmed by TEM and hardness. Back-calculated plastic strain values via KAM agree within 5 percentage points, indicating standard EBSD alone is insufficient to determine absolute plastic strain in AM alloys, but KAM and GND offer the most practical metric for semi-quantitative assessment.
This study describes a novel design and manufacturing approach for an optimized two-phase aluminum matrix, silicon carbide-reinforced cellular metamaterial composite with a low coefficient of thermal expansion (CTE). The design was generated with Bayesian optimization to obtain a periodic cellular pattern with the minimum coefficient of thermal expansion. The manufacturing was achieved via binder jetting additive manufacturing, followed by liquid aluminum infiltration. The barrier coating layer of Si-SiO2 and the cooling rate after infiltration were found to be critical for suppressing the reaction between the two phases and maintaining the silicon carbide phase. A comparable study found that a proactive cooling rate as high as 20°C/min could maintain a phase fraction of silicon carbide up to 12wt.% in the manufactured composite, leading to minimized CTE values in multiple cycles of a single sample and repeatable values across various samples. The thermal cycling test validated the performance of the manufactured composite at high temperatures up to 350 °C. This study explored the design-manufacturing-test route for a novel metallic metamaterial composite, opening a wide research direction for advanced materials in harsh environments.
A WE43 Mg alloy with heterogeneous microstructure, featuring grain sizes ranging from 25 μm to 1 μm arranged in alternating bands, was manufactured via solid-state additive friction stir deposition technique. The alloy exhibits a favourable strength-ductility balance in tension, with a yield strength of 201 ± 13 MPa, an ultimate tensile strength of 270 ± 5 MPa, and a uniform elongation of 17.1 ± 2.0%, outperforming many additively manufactured Mg alloys reported to date. The dominant deformation mechanisms were ascertained at different length scales, and involve basal slip, extension twinning, and limited non-basal slip, which operates across all grain size populations, but their relative activities are sensitive to grain size. The gradual yielding of grains with different sizes—from coarse to fine—induces pronounced strain partitioning and dislocation accumulation at their interfaces. This synergistic interaction sustains strain hardening during deformation and effectively alleviates the conventional strength-ductility trade-off. These findings provide multiscale insights into the deformation behaviour and strain-distribution mechanisms of heterogeneous Mg alloys processed by additive manufacturing.
In this study, the mechanical performance of complex Ti-6Al-4V brackets with a geometry that could not be fabricated with conventional processing methods was investigated. The brackets were designed to investigate the combined effects of stress state and the presence of pores on the structural and fracture behavior of complex, multi-member components that can be manufactured with additive manufacturing. A pore size-dependent Mohr-Coulomb model was used to calculate fracture locations, load carrying capacities, and pore-insensitive regimes below which pores had a negligible effect on mechanical performance. For complex structures such as the one under consideration, the load carrying capacity was shown to be more sensitive to stress state and pore size than for simpler coupon samples. The combined effects of pore size and stress state were shown to be more significant than the sum of their individual contributions, demonstrating the importance of capturing their effects simultaneously when modeling fracture, especially in the context of multi-member components. The sensitivity of the mechanical performance of the Ti-6Al-4V brackets to stochastic pore sizes typically encountered in practice was simulated using a Monte Carlo analysis, quantitatively showing the reduction of mean capability of the structure and the reduction of reliability due to small stochastic pores. As AM is increasingly used for structural applications, this study demonstrates the importance of fracture modeling in conjunction with process control and nondestructive evaluation for the assessment of structural performance and reliability.
