| Abstract Scope |
Artificial intelligence is reshaping materials innovation, but realizing its full impact requires advances in both materials discovery and manufacturing. AI-driven approaches—including foundation models, generative design, and autonomous experimentation—are rapidly expanding the search space for catalysts, battery materials, magnets, and other energy technologies. At the same time, Integrated Computational Materials Engineering (ICME) continues to provide a robust framework for optimizing processing–structure–property relationships within established material systems, enabling faster translation from concept to application.
Equally important is accelerating manufacturing itself. Process intensification and vertically co-designed manufacturing can reduce cost and deployment time by simultaneously optimizing feedstocks, processing routes, and product performance. Rather than treating purification, synthesis, and manufacturing as independent steps, vertical co-design begins with available domestic resources and a minimum viable performance target, enabling unnecessary processing steps to be eliminated while improving supply-chain resilience. Such vertically integrated approaches can initially satisfy domestic sourcing requirements and ultimately become globally cost-competitive through simplified processing and scale. Together, AI-enabled materials design and manufacturing innovation offer complementary pathways to shorten development cycles, strengthen critical material supply chains, and accelerate commercialization of next-generation energy technologies. |