Researchers at Delft University of Technology were among the first to design a new material with Artificial Intelligence (AI) and computer simulations without experimental trial-and-error (in 2019). The MACHINA (Machine Intelligence Advances for Materials) Lab is trying to build on this success by uniting AI developers with AI practitioners, creating a new route for designing novel materials and AI algorithms.
AI is key to create the next generation of materials because they need to be adaptive, multi-purpose and tunable. Such complex material behaviour requires the consideration of too many design possibilities for the human mind to process, but not for machine learning algorithms. These methods create an opportunity to invert and improve the design process by shifting from experiments to data-driven design with computer simulations, even if the computer models are missing some information. The essential requisite is that ‘enough’ data about the problem of interest is available. Given enough data, AI can provide a treasure map and the scientist can then find the treasure (new material).
The MACHINA Lab focuses on different aspects of the data-driven process, including speeding up material simulations, as well as exploring new machine learning and optimisation methods that facilitate analysis and design. Currently, these new algorithms are being used to design environmentally friendly plastics and metamaterials for biological applications, i.e. materials with exotic properties (such as supercompressibility) that emerge from exploring new geometries and new combinations of constituents.
The use of AI in designing materials is still in a very early stage but could in time mean a small revolution. These approaches are applicable to a very broad range of materials, so they can help solve some of humanity’s energetic, environmental and health issues. Hopefully, MACHINA will take some small steps towards solving some of these big challenges.