Page 7: 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

Neutrons dive deep to help protect US nuclear submarines

America's national security relies in part on the U.S. Navy's nuclear-powered submarines, which can operate more than 800 feet below the ocean's surface. At such dark, unforgiving depths, the crew's survival depends on the ...

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