ADVANCED MATERIALS & PROCESSES | MARCH 2024 56 3D PRINTSHOP LARGE-SCALE RAPID ALUMINUM PARTS Liquid metal printing (LMP), an additive manufacturing technique de- veloped by researchers at MIT, can produce parts at least 10 times faster than comparable processes, and more efficiently. The process deposits molten aluminum along a predefined path into a bed of tiny glass beads. The aluminum quickly hardens into a 3D structure, producing large-scale parts such as table legs and chair frames in a matter of minutes. The technique does sacrifice resolution for speed and scale. While it can print components that are larger than those typically made with slower additive techniques, and at a lower cost, it cannot achieve high resolutions. The researchers note that parts produced with LMP could be suitable for applications in architecture, construction, and industrial design, where components of larger structures often don’t require extremely fine details. The method could also be used effectively for rapid prototyping with recycled or scrap metal. During LMP, the aluminum is held at a high temperature in a graphite crucible, and then molten material is gravity-fed through a ceramic nozzle into a print bed along a preset path. The scientists found that the larger the amount of aluminum they could melt, the faster the printer can go. And by injecting the molten material directly into a granular substance, the researchers don’t need to print supports to hold the aluminum structure as it takes shape. Moving forward, the researchers want to keep improving the machine so they can enable consistent heating in the nozzle to prevent material from sticking, and also achieve better control over the flow of molten material. web.mit.edu. FINDING DEFECTS USING SOUND A team from EPFL in Switzerland is detecting defects in laser powder- bed fusion (LPBF) printed parts by listening to and comparing the sounds a printer makes during a flawless print and one with irregularities. In a joint venture with the Paul Scherrer Institute (PSI) and the Swiss Federal Laboratories for Materials Science and Technology (Empa), the EPFL team formulated an experimental design that melded operando x-ray imaging experiments with acoustic emission measurements. The experiments were conducted at the TOMCAT beamline of the Swiss Light Source at PSI, with a miniaturized LPBF printer. An ultra-sensitive microphone positioned inside the printing chamber pinpointed distinct shifts in the acoustic signal during regime transitions, thereby directly identifying defects during manufacturing. A pivotal moment in the research was the introduction of an adaptive filtering technique by signal processing expert Giulio Masinelli from Empa. “This filtering approach,” Masinelli emphasized, “allows us to discern, with unparalleled clarity, the relationship between defects and the accompanying acoustic signature.” Unlike typical machine learning algorithms, which excel at extracting patterns from statistical data but are often tailored to specific scenarios, this approach provides broader insights into the physics of melting regimes while offering superior temporal and spatial precision. The findings suggest the potential for early detection and correction of defects, enhancing product quality in potential applications such as aerospace and precision engineering. www.epfl.ch. Liquid metal printing produces large-scale parts like table legs and chair frames in a matter of minutes. Courtesy of MIT Self-Assembly Lab. A graphic of the experimental setup for listening for printing defects. Courtesy of EPFL/Titouan Veuillet.
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