Radical AI — Accelerating Materials R&D

Materials research and development is an immense and enormously important market across various fields of technology, including semiconductors, aerospace, and automotive. However, conventional materials research relies on an outdated trial-and-error approach, which is a very slow and costly process. At Radical AI, we are revolutionizing the way materials are discovered by building a continuous loop of computation and experimentation driven by artificial intelligence. Specifically, we train accurate and efficient atomistic foundation models on large DFT databases to enable molecular dynamics simulations at 70 million times the speed of DFT. Promising materials are then synthesized and characterized in our laboratories, in an automated and autonomous way. Feedback from computational and experimental data is leveraged by our generative AI models to accelerate the discovery of new materials. As an example, I'll focus here on the case of bulk metallic glasses and highlight the promise and challenges of this class of materials.