Researchers at Xi'an Jiaotong University built a closed‑loop AI framework centered on a large language model that generates and evaluates thousands of carbon structures, rapidly discovering ultra‑hard, highly anisotropic and novel carbon allotropes such as C16_3, C12 and C8 within minutes.
EMSeek, a modular multi‑agent platform from Cornell, integrates perception, structural reconstruction, property prediction, and literature reasoning to automate electron microscopy analysis across 20 material systems and five tasks, achieving up to twice the speed of Segment Anything, over 90% structural similarity, and a 50‑fold reduction in processing time compared with expert workflows, while requiring only about 2 % labeled data for calibration.
MOF‑ChemUnity constructs a scalable, extensible knowledge graph that links millions of MOF names and synonyms to over 15,000 crystal structures using LLM‑driven entity matching, enabling accurate, explainable AI‑assisted material discovery, water‑stability prediction, expert recommendation validation, and graph‑enhanced retrieval across diverse applications.
Former OpenAI research VP Liam Fedus and DeepMind veteran Ekin Dogus Cubuk founded Periodic Labs to build an AI‑driven scientific platform that combines autonomous robotic labs, high‑fidelity simulations, and LLM assistants, secured $300 million in seed funding, and assembled a team of over 20 elite researchers to accelerate discovery of room‑temperature superconductors and other materials.
