Ultrahigh Specific Strength by Bayesian Optimization of Carbon Nanolattices
Ultrahigh Specific Strength by Bayesian Optimization of Carbon Nanolattices
Just a moment...
Andi's writeup
Researchers at the University of Toronto and Korea Advanced Institute of Science and Technology (KAIST) have developed carbon nanolattices with unprecedented strength-to-weight ratios using machine learning optimization[1]. The team achieved a specific strength of 2.03 MPa m³ kg⁻¹ at densities below 215 kg m⁻³, creating materials as strong as carbon steel but with the density of Styrofoam[2].
The breakthrough came through multi-objective Bayesian optimization of lattice designs combined with two-photon polymerization 3D printing. This approach improved strength by 118% and Young's modulus by 68% compared to traditional designs[3]. By reducing strut diameters to 300 nm, the researchers produced high-purity pyrolytic carbon structures containing 94% sp²-bonded carbon[3].
The team successfully scaled production using multi-focus two-photon polymerization to create millimeter-scale metamaterials containing 18.75 million nanolattice cells[3]. "If you were to replace components made of titanium on a plane with this material, you would be looking at fuel savings of 80 litres per year for every kilogram of material you replace," said Peter Serles, the study's first author[4].
[^1]: 3D Printing Industry - Optimized Carbon Nanolattices Achieve Record Strength
[^2]: Technology Networks - Machine Learning Designs Materials As Strong As Steel and As Light As Foam
[^4]: Science Daily - Strong as steel, light as foam: High-performance, nano-architected materials