Professor Ju Li’s group investigates the mechanical, electrochemical, and transport behaviors of materials as well as novel means of energy storage and conversion. His research has led to advances in materials with applications in nuclear energy, batteries, and electrolyzers—and near- and long-term implications for decarbonizing the planet. His group also works on various aspects of computing, from the development of the first universal neural network interatomic potential to analog neuromorphic computing hardware and quantum information processing.
Professor Li earned a BS in physics at the University of Science and Technology of China in 1994, followed by a PhD in nuclear engineering at MIT in 2000. Before joining DMSE as a faculty member in 2011, Professor Li spent nine years at the Ohio State University and the University of Pennsylvania. He is the chief organizer of MIT A+B Applied Energy Symposia, which aims to develop solutions to global climate change challenges.
Nanosecond protonic programmable resistors for analog deep learning
Developed programmable resistors, or artificial synapses—devices that can be used to build analog deep learning processors. Compatible with silicon fabrication techniques, these artificial synapses increase the speed and reduce the energy needed to train neural network models.
Thermally drawn rechargeable battery fiber enables pervasive power
Developed a rechargeable lithium-ion battery in the form of a self-contained ultra-long fiber that’s weavable and washable. The test produced the world’s longest flexible and waterproof fiber battery, at 140 meters long.