Led by Cornell University, NSF Artificial Intelligence Materials Institute (AI-MI) is accelerating the discovery of next-generation materials essential for energy, sustainability and quantum technologies.

By bringing together computer scientists, materials researchers and data scientists, AI-M tackles knowledge- and data-centric challenges to advance AI and materials science. The institute integrates data generation, AI analysis and rapid experimental feedback to dramatically reduce the time it takes to discover new materials – from months to days – and to establish reproducible, reusable workflows for the broader research community.

To support this work, AI-MI plans to create the AI Materials Science Ecosystem (AIMS-EC) – an open, cloud-based portal that integrates a science-ready large language model with data from experiments, simulations, images and scientific literature. Using AIMS-EC, the institute will discover 2D moiré structures for robust qubits, learn descriptors that can guide the design of new superconductors, discover new functional soft materials and mixtures and identify functional peptides for the removal of microplastics from the environment.

Moreover, AI-MI will accelerate how materials are made using data-driven optimization of film growth and self-driving labs. Through partnerships with high schools, universities, and industry, AI-MI will educate and train students at all levels and open new career pathways at the intersection of AI and physical sciences.