Research Infrastructure: MIP: Materials AI and Transformation through Research Infrastructure for eXtreme environments: an NSF Materials Innovation Platform (MATRIX-MIP)

Nontechnical Description: The Materials AI and Transformation through Research Infrastructure for eXtreme environments (MATRIX) Materials Innovation Platform (MIP) provides open access to advanced tools and expertise for discovering and developing materials that can operate in extreme environments. Many technologies critical to energy production, transportation, national security, and advanced manufacturing require materials that can withstand combinations of very high temperatures, mechanical stress, corrosive conditions, and radiation. Existing materials often face tradeoffs between strength, durability, manufacturability, and cost. MATRIX-MIP addresses these challenges by bringing together materials synthesis, manufacturing, characterization, testing, modeling, and artificial intelligence (AI) within a single user-centered platform. Through open user access, workforce development activities, data sharing, and AI-enabled knowledge tools, the platform expands the national capacity for materials innovation and accelerates the translation of scientific discoveries into technologies that benefit society. Targeted in-house research develops user-center tools and advances understanding of complex materials under extreme conditions. Technical Description: MATRIX-MIP investigates how chemical and structural complexity across multiple length scales influences the processing, evolution, and performance of high-temperature structural materials, including refractory metals, ceramics, and composites. The platform integrates high-throughput synthesis, additive manufacturing, binder jetting, spark plasma sintering, advanced characterization, in-situ diagnostics, extreme-environment testing, computational modeling, and AI-guided materials design into a closed-loop materials discovery framework. Unique capabilities include multi-material additive manufacturing with real-time process monitoring, autonomous-ready experimental workflows, and advanced synchrotron X-ray facilities at the Advanced Photon Source for observing materials during synthesis, heat treatment, oxidation, and corrosion. Computational capabilities include thermodynamic modeling, machine-learning interatomic potentials, mesoscale simulations, active learning, uncertainty-aware machine learning, and AI-enabled knowledge management. MATRIX-MIP supports a broad user community through multiple access modes, staff-assisted experimentation, training workshops, hackathons, summer schools, and implementation of Findable, Accessible, Interoperable, and Reusable (FAIR) data and model practices. The platform serves as a national resource for understanding and engineering complex structural materials for demanding operating environments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.