Materials funnel 2.0 – data-driven hierarchical search for exploration of vast chemical spaces

We propose a novel HTCS accelerated inverse design in a very large materials space combining the benefits of generative modeling, computationally efficient machine learning surrogate and high-quality physics-based simulation.