Maximizing Nitinol Flexibility Through Algorithm-Driven Design and L-PBF

In the world of smart materials, nitinol stands out for its unique functional properties. This nickel-titanium alloy is known for its shape memory and superelasticity. While these capabilities are highly valued in biomedical and aerospace applications, processing nitinol through powder bed fusion (L-PBF) often compromises its mechanical performance. Until now, additively manufactured nitinol parts have shown only about half the recoverable strain compared to components produced by traditional methods.

To overcome this technical limitation, a team from the IMDEA Materials Institute and the Polytechnic University of Madrid (UPM) decided to stop trying to “fix” the material itself and instead optimize its architecture. Their approach focuses on designing intertwined metal structures, or metamaterials, that behave like a textile. Here’s how they achieved it.

Carlo Aguilar holding the 3D-printed metamaterial.

The central problem addressed by the study, published in Virtual and Physical Prototyping, is the mechanical limitation of nitinol after printing. When nitinol is printed, the microstructure of the part often does not match the resilience of conventionally produced material. Instead of searching for a new alloy, the researchers adopted an algorithm-driven design framework to create interlocking metamaterials.