Page 11: 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.

Energy & Green Tech

New aluminum alloy can boost U.S. auto supply chain

A wave of aluminum auto body scrap is set to enter salvage systems over the next decade. This scrap is often too impure to safely be reused in new critical automotive parts, limiting its value. That's changing thanks to a ...

Engineering

A path to higher as-built ductility in printable aluminum alloys

Most aluminum alloys made through additive manufacturing (AM) have very limited as-built ductility, which may lead to the adoption of more expensive, heavier alternative materials in applications such as automotive and aerospace ...

Engineering

Students develop novel multi-metal 3D printing process

Students at ETH Zurich have developed a laser powder bed fusion machine that follows a circular tool path to print round components, which allows the processing of multiple metals at once. The system significantly reduces ...

Robotics

Developing self-deploying material for next-gen robotics

The field of robotics has transformed drastically in this century, with a special focus on soft robotics. In this context, origami-inspired deployable structures with compact storage and efficient deployment features have ...

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