Page 14: Research news on Data-driven alloy design

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

Highly twisted metamaterial rods store large amounts of energy

An international research team coordinated at KIT (Karlsruhe Institute of Technology) has developed mechanical metamaterials with a high elastic energy density. Highly twisted rods that deform helically provide these metamaterials ...

Engineering

Precision analysis method of tooth profile in gear skiving process

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 ...

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