Researchers use machine learning to detect defects in additive manufacturing." ScienceDaily. ScienceDaily, 4 June 2024. <www.sciencedaily.comUniversity of Illinois Grainger College of Engineering. . Researchers use machine learning to detect defects in additive manufacturing.
Researchers have 3D printed a dual-phase, nanostructured high-entropy alloy that exceeds the strength and ductility of other state-of-the-art additively manufactured materials, which could lead to ... Researchers have designed and additively manufactured a first-of-its-kind aluminum device that enhances the capture of carbon dioxide emitted from fossil fuel plants and other industrial ...
Researchers have set a new world record: they 3D printed complex objects with higher cellulose content than that of any other additively manufactured cellulose-based parts. To achieve this, they used ... To further shrink electronic devices and to lower energy consumption, the semiconductor industry is interested in using 2D materials, but manufacturers need a quick and accurate method for detecting ...Public Have No Difficulty Getting to Grips With an Extra Thumb, Study Finds