Data-driven alloy design integrates computational methods, machine learning, and advanced manufacturing to create metallic alloys and composites with tailored properties. Emphasis is placed on metal 3D printing and related additive processes as platforms for controlling solidification, microstructure, and defect formation in systems such as aluminum, titanium, magnesium, high-entropy, and shape-memory alloys. By linking processing parameters, atomic-scale mechanisms, and multiscale models to mechanical, thermal, and environmental performance, this area accelerates discovery and optimization of structural and functional materials for demanding applications.
Engineering
The Nano Materials Research Division at the Korea Institute of Materials Science (KIMS), led by Dr. Tae-Hoon Kim and Dr. Jung-Goo Lee has successfully developed a grain boundary diffusion process that enables the fabrication ...
Mar 14, 2025
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288
Engineering
A new approach to gear skiving, a specialized machining technique for producing internal gears, could improve the speed and accuracy with which gear teeth are formed. The work, described in the International Journal of Abrasive ...
Mar 10, 2025
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32
Engineering
Producing high-performance titanium alloy parts—whether for spacecraft, submarines or medical devices—has long been a slow, resource-intensive process. Even with advanced metal 3D-printing techniques, finding the right manufacturing ...
Mar 7, 2025
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142
Robotics
Energy remains a significant factor in industrial production processes. High levels of energy consumption make production more expensive and exacerbate the climate crisis.
Mar 6, 2025
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67
