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Decarbonizing transportation, the grid, and heavy industries depends on the success of both short- and long-duration energy storage solutions. Through novel material design and chemistry, my lab addresses critical challenges in developing affordable, sustainable, and reliable energy storage technologies. For short (to medium)-duration storage, we design and develop new cathode materials for sodium-ion batteries rich in manganese and iron. Our goal is to achieve energy densities comparable to lithium-ion batteries but at lower costs, without relying on critical minerals, thereby accelerating the transition to more sustainable energy storage. For long-duration storage, we have developed groundbreaking pathways for producing hydrogen (H₂) and ammonia (NH₃) using subsurface chemistry. By harnessing redox reactions on Fe-rich rocks and utilizing the Earth's natural heat and pressure, we demonstrate the potential for stimulated geological H₂ and NH₃ production. These methods achieve near-zero CO₂ emissions while remaining cost-competitive with existing technologies. Our work integrates advanced materials design with sustainable chemistry to provide scalable, impactful solutions for a decarbonized future.
Gayathri Srinivasan Executive Director, MIT Corporate Relations
Brian W Anthony Principal Research Scientist, Department of Mechanical Engineering Associate Director, MIT.nano Director of Technical Operations, Center for Clinical and Translational Research
Industry is undergoing a major transformation, shifting from automated to autonomous operations. The key to making this happen is the integration of digital technologies, including sensors, data, computing power, and information systems. At the heart of this shift are digital twins—virtual models that represent materials, processes, supply chains, and production lines. These digital replicas allow for simulation, monitoring, and improvement of operations in real-time using sensor data. When digital twins are combined with real-time control systems and machine learning, operations and factories become smarter and more adaptive. Real-time data flows from sensors to digital models and ML algorithms, enabling predictive maintenance, waste reduction, and optimizing production. A data-in-context connected ecosystem creates a highly efficient, data-driven environment in manufacturing and in mining.