Page 13: 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.

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 ...

Engineering

New DuAlumin-3D alloy enhances high-performance automotive parts

Scientists at Oak Ridge National Laboratory have advanced the use of DuAlumin-3D, an innovative aluminum alloy, in high-temperature automotive components, significantly expanding the possibilities of additive manufacturing.

Software

New dataset for smarter 3D printing released

Oak Ridge National Laboratory's Peregrine software, used to monitor and analyze parts created through powder bed additive manufacturing, has released its most advanced dataset to date.

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