Researchers at the University of Toronto have developed a groundbreaking material that combines the strength of steel with the lightness of polystyrene foam, using machine learning and nano-3D printing. The new material boasts ultra-high specific strength and scalability, making it an ideal candidate for aircraft and spacecraft applications.
According to Peter Sells, lead researcher on the project, the “smaller is stronger” effect can be achieved by combining high-performance geometries at nanoscale sizes. By employing a multi-objective Bayesian optimization machine learning algorithm, Sells and his team designed an improved material that excels in stress distribution and strength-to-weight ratio.
The KAIST team used simulated shapes to predict optimal nanoscale shapes, which were then printed using a nanoscale 3D printer at the University of Toronto’s Centre for Research and Applications of Fluid Technology. The resulting prototype material is five times stronger than titanium and can float on a soap bubble due to its remarkable lightness.
The new material has significant implications for aerospace engineering, with potential applications in aircraft, helicopters, and spacecraft. According to Sells, replacing titanium parts with the new material could save 80 litres of fuel per year for every kilogram of material replaced.
Future research will focus on further improving scale-up and cost-effectiveness of these material designs, while exploring new designs that reduce material density while maintaining high strength and stiffness.
Source: https://gigazine.net/gsc_news/en/20250130-strong-light-machine-learning