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

Composite metal foam could lead to safer hazmat transportation

A new study finds that composite metal foam (CMF) can withstand tremendous force—enough to punch a hole in a railroad tank car—at much lower weight than solid steel. The finding raises the possibility of creating a safer ...

Engineering

Alloys that 'remember' their shape can prevent railroad damage

In railroad tracks, rail ties hold the rails in place and ensure that their separation does not change. Modern concrete ties warp and crack through repeated use, leading to safety concerns including derailment if not regularly ...

Engineering

Can smoother surfaces prevent hydrogen embrittlement?

Hydrogen is a promising fuel for developing sustainable industrial processes, but its use is hindered by hydrogen embrittlement—a phenomenon that weakens metals and can cause sudden failure. Now, researchers from Japan have ...

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