Using AI-enabled Autonomous Experimentation (AI/AE) to Accelerate the Transition from Sustainable Semiconductor Materials R&D through Deployment: a CHIPS for America Viewpont

Using AI-enabled Autonomous Experimentation (AI/AE) to Accelerate the Transition from Sustainable Semiconductor Materials R&D through Deployment: a CHIPS for America Viewpont.

AI/AE has emerged as a potentially game-changing approach to accelerate materials discovery and development. The CHIPS for America program has issued a Notice of Funding Opportunity (NOFO) titled CHIPS AI/AE for Rapid, Industry-informed Sustainable Semiconductor Materials and Processes (CARISSMA) that aims to create collaborations between academia and the private sector that are university-led, industry-informed, and relevant to sustainable semiconductor materials and manufacturing. These collaborations should support the long-term viability of domestic semiconductor manufacturing by accelerating the discovery, design, synthesis, and deployment of new materials and processes; developing and connecting cutting-edge AI/AE techniques, know-how, and infrastructure; and developing new researchers needed to meet the industry’s technological, economic, and sustainability goals.