Adjacent Space: Materials Design

This project develops an AI platform that revolutionizes materials discovery by enabling inverse design - starting with desired properties and generating novel material structures to achieve them. The system employs multimodal denoising diffusion models trained on curated materials databases to explore vast chemical spaces and propose candidate materials optimized for specific applications like energy conversion and electronics. Using Imperial College London's simulation facilities and automated experimental setups, the platform integrates iterative validation workflows to rigorously test AI-generated predictions against real-world performance metrics.