Researchers at the University of Toronto’s Faculty of Applied Science & Engineering have developed a new type of nanomaterial that combines the strength of carbon steel with the lightness of Styrofoam. By using machine learning, the team created nanomaterials with unprecedented strength, weight, and customizability. The material is composed of tiny building blocks measuring just a few hundred nanometers, making it incredibly strong and lightweight.
The team used a machine learning algorithm to optimize the geometry of the nanomaterials, predicting optimal designs and improving the strength-to-weight ratio. This process was accelerated, requiring only 400 data points compared to traditional methods which may require 20,000 or more. The team was surprised by the improvements, which went beyond the training data, allowing them to predict entirely new lattice geometries.
The potential applications of these materials are vast, including aerospace and automotive industries. The researchers envision using these materials to create ultra-lightweight components for planes, helicopters, and spacecraft, potentially reducing carbon footprint and energy consumption.