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

Adjusted heating process makes batteries last longer

To make batteries that last longer, scientists are creating internal battery structures that don't degrade as quickly as current designs do. In fact, the reason many lithium-ion batteries ultimately fail is that their cathodes, ...

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