Molten metal jetting (MMJ) is an additive manufacturing (AM) method where droplets of molten metal are used to build parts. Like most AM technologies, MMJ is typically used to build stand-alone parts rather than add onto existing parts. However, the droplet-wise deposition method of MMJ is inherently compatible with the ability to build on existing parts. Here, we utilize MMJ to “repair” machined damage on cast aluminum parts. A commercial MMJ system was used to fill in varied but defined groove geometries to find optimal shapes amenable to repair with MMJ. Subsequently, grooves were cut into tensile specimens and back-filled (repaired) using MMJ. Tensile tests indicate that MMJ repair restores significant strength to samples despite the distinct microstructure and void structures present in the repaired section. Repaired samples demonstrated tensile strengths ∼72% of the as-received material, compared to UTS of ∼33% for damaged samples. These results indicate that MMJ is a viable method to repair parts where other repair methods may be impractical.

Soft robotics have become increasingly popular as a versatile alternative to traditional robotics. Magnetic composite materials, which respond to external magnetic fields, have attracted significant interest in this field due to their programmable two-way actuation and shape-morphing capabilities. Additive manufacturing (AM), also known as 3D printing, allows for the incorporation of different functional composite materials to create active components for soft robotic systems. However, current AM methods have limitations, especially when it comes to printing smart composite materials with high functional material content. This is a key requirement for enhancing responsiveness to external stimuli. Commonly used AM methods for smart magnetic composites, such as direct ink writing (DIW), confront challenges in achieving discontinuous printing, and enabling multi-material control at the voxel level, while some AM techniques are not suitable for producing composite materials. To address these limitations, we employed high-viscosity drop-on-demand (DoD) jetting and developed versatile programmable magnetic composites filled with micron-sized hard magnetic particles. This method bridges the gap between conventional ink-jetting and DIW, which require inks with viscosities at opposite ends of the spectrum. This high-viscosity DoD jetting enables continuous, discontinuous, and non-contact printing, making it a versatile and effective method for printing functional magnetic composites even with micron-sized fillers. Furthermore, we demonstrated stable magnetic domain programming and two-way shape-morphing actuations of printed structures for soft robotics. In summary, our work highlights high-viscosity DoD jetting as a promising method for printing functional magnetic composites and other similar materials for a wide range of applications.

This study seeks an early prediction method of crack failure location and orientation due to low cycle fatigue in additively manufactured metallic cellular materials by leveraging experimentally observed accumulation of plastic deformation. To study this, a novel spatial-temporal approach for analyzing Infrared Thermographic (IRT) video was developed to detect heat generated by local plastic deformation. The method was validated experimentally by conducting fully reversed low cycle fatigue tests of Inconel 718 (IN718) honeycomb specimens manufactured using Laser Powder Bed Fusion (LPBF). Using the approach developed, results showed that localized heating due to plastic work could be detected and used for early prediction of the most probable path, and orientation of crack propagation. Furthermore, the method developed was found to be able to predict these results within the first 1.5% of the total life of the specimen apriori to crack initiation.

With the recent implementation of additively manufactured parts into industrial applications, there is a dire need for nondestructive evaluation methods to qualify if these components are fit for service due to their sensitivity to processing conditions. The Impulse Excitation Technique (IET) is applied to additively manufactured Ti-6Al-4V bending specimens to determine natural frequencies and damping properties in order to predict fatigue performance relative to specimens fabricated with different processing parameters. From the damping and natural frequency results, it was found that the specimens, fabricated with intentional underheating to induce lack of fusion defects, had the lowest damping value in the pristine condition and the highest natural frequency. For the three batches of specimens tested, it was determined that the lack of fusion specimens had the best fully-reversed bending fatigue performance with the highest fatigue limit (297 MPa) and longest fatigue lives as compared to the other two batches, implying a relation of decreased fatigue life with increased material damping in the pristine condition. The theory of the IET related to materials is presented with damping and fatigue results, as well as microstructural analysis and fractography of three specimens batches fabricated with different processing parameters.

Process parameters optimization in additive manufacturing (AM) is usually required to unlock superior properties, and this is often facilitated by modeling. In electron beam powder bed fusion (E-PBF), the preheat temperature is an important parameter to be optimized as it significantly influences the microstructure and properties. Here we compare the effect of two preheat temperatures (1000 and 950°C, above and below δ-phase solvus temperature) on the microstructural evolution of E-PBF IN718 Ni-based superalloy. Using thermal and thermo-kinetic modeling, we predict microstructural changes and compare them with experimental findings. A decrease of only 50°C in the preheat temperature has a low impact on the solidification microstructure with a slight reduction in columnar grain width. In the solid-state, higher preheating causes intergranular δ-phase precipitation, contributing to a higher γ" precipitation potential, formation of co-precipitates, and higher hardness. The lower preheat temperature induces intergranular and intragranular δ-phase precipitation, reducing the γ" precipitation potential and hardness. The chemical composition of γ' and γ" is largely unaffected by the preheat temperature variation. These insights underscore the importance of preheat temperature optimization in microstructure design and property control during E-PBF.

High-nitrogen martensitic stainless steels, such as X30CrMoN15 (0.3 to 0.5 mass% nitrogen), exhibit an excellent combination of strength and corrosion resistance, making them well-suited for applications in the medical technology and aerospace industry. The qualification of these steels for additive manufacturing (AM) could generate new application areas where AM, due to its process-specific advantages, could offer added value compared to conventional manufacturing methods. However, the laser powder bed fusion (PBF-LB/M) of high-nitrogen alloyed steels is challenging due to the high tendency for gas pore formation, resulting from the limited nitrogen solubility in the steel melt. In this work, a new process route for AM of a high nitrogen containing X50CrMoV15 martensitic stainless steel is presented, which consists of a process combination of powder nitriding, PBF-LB/M and subsequent hot isostatic pressing (HIP) with integrated quenching. Gas nitriding is used to achieve a nitrogen content in the starting powder that exceeds the maximum solubility in the melt. Although the nitrogen content decreases during the PBF-LB/M process, the high solidification and cooling rates prevent the melt from reaching equilibrium nitrogen levels, resulting in a nitrogen content above the solubility limit in the final PBF-LB/M state. The pores formed during the process are closed through HIP, which also allows hardening via integrated gas quenching. With an additional cryogenic treatment, the process produces a fully dense steel with 75% martensitic structure and 0.246 mass% nitrogen. Further optimization opportunities have been identified and are discussed.

Simulation is one of the most widely used methods for process optimization towards improved part quality in Additive Manufacturing (AM), particularly for metal parts. However, due to the nature of the AM processes and the complex phenomena that occur, simulations that are capable of providing a detailed overview of the physical mechanisms demand considerable computational resources and time. In this study, a numerical approach is presented, which can be applied to any implicit numerical thermal simulation for AM, allowing for a significant decrease in computational time (higher than 70%) with minimal impact on accuracy. This is achieved by combining space partitioning, enabled by a boundary condition that was developed, with dynamic mesh adaptation in the x-, y-, and z-axis. The methodology is described in detail and both the decrease in computational time and the accuracy of the developed approach are validated in a computational case study, as well as using experimental results.

Only a limited aluminium material palette is currently available for L-PBF processing, especially for high strength aluminium alloy. Unmodified Al7075 suffers from hot cracking making it nearly impossible to process by L-PBF. Adding some grain refiner to Al7075 solves this issue of hot cracking. However, this alloy still presents difficulties to be processed with densities above 99.5%. In this study, the unconventional pre-sintering scanning strategy is applied to process 99.9% density Al7075+1.8%Zr. For this scanning strategy, each layer is scanned twice with different power, i.e. it is first scanned with half the power selected for the second scan. This specific strategy remelts potential defect generated by the first scan and reduces lack of fusion pores. These two phenomena lead to high density L-PBF Al7075+1.8%Zr and pave the way to higher densities for high strength aluminium alloys.