Researchers at the University of Toronto have made a significant breakthrough in designing ultralight materials with surprising strength . By applying machine learning and nanoscale 3D printing , the team has managed to create nanoarchitectural materials that combine the strength of steel with a density as low as that of polystyrene.
The power of carbon nanonetworks
The team, led by Professor Tobin Filleter and researcher Peter Serles, has focused its efforts on the design of carbon nanonetworks, three-dimensional structures composed of repetitive nanometric-sized units.
[post_relacionado]These building blocks, with a thickness of no more than hundreds of nanometers, allow the resulting materials to have unique structural behavior at tiny scales.
Ultralight and high-strength materials
Using a multi-objective Bayesian optimization algorithm, researchers have succeeded in designing ultralight materials with exceptional strength. This machine learning technique has allowed the team to improve existing geometries and discover new configurations to maximize the strength-to-weight ratio.
The results are impressive: these new materials have five times the strength of titanium per kilogram of material, making them an ideal choice for applications requiring high durability and low weight.
Impact on the aerospace industry and beyond
Advances in these nanoarchitectural materials could have a significant impact on a range of industries. In the aerospace field, for example, replacing titanium components with these materials could lead to fuel savings of up to 80 litres per year for every kilogram of material replaced.
This not only improves fuel efficiency, but also reduces the carbon footprint of flights – a major advantage in the fight against climate change.
The precision 3D printer as a key tool
A key factor in this achievement has been the use of a two-photon 3D printer, a technology that allows prototyping nanonetworks with extreme precision . This nanoscale printing capability was essential to experimentally validate the designs optimized by the machine learning algorithm, ensuring that the printed materials met performance expectations.
The University of Toronto team, together with international collaborators from institutions such as the Karlsruhe Institute of Technology (KIT) in Germany and MIT in the United States, continues to explore new ways to improve the scalability of these ultralight materials.
As they refine their designs, the researchers hope these advances can be applied to macroscale components, allowing them to be cost-effectively produced for a variety of industrial applications.
Follow us on social media and don’t miss any of our posts!
YouT ube LinkedIn Facebook Insta g ram X (Twitter) TikTok
Source: University of Toronto
Photo: Shutterstock