Materials of the future will rely on nanostructures painstakingly tailored to design constraints and reach unprecedented levels of performance. In order to design these new materials, accurate simulations of material behavior across the scales are needed. Yet, even one of these models currently takes months to run on conventional computers.

The goal of the SLIMM lab is to facilitate virtual material testing across the scales by combining Bayesian machine learning and multiscale solid mechanics into new smart material models and learning frameworks.

Why virtual testing through smart multiscale models?

• Speed: Designing new materials without waiting for years for simulations to run
• Accuracy: Precise nanostructure optimization and deeper knowledge on material behavior
• Sustainability: Fewer destructive experiments needed and lower energy use through faster simulations

The SLIMM Lab is part of the TU Delft AI Labs programme.