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.

Key Publications

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.

Deep learning, a subset of artificial intelligence (AI), is key for successful automation, facilitating many analytical and computational tasks without human intervention. But training these models using current computers is associated with unsustainably high energy demand. Low-energy alternatives need to be found.

Deep learning processors that can execute computations fast while using much less energy can satisfy the growing need for AI while still meeting sustainability goals. Faster training of neural networks means faster deployment of deep learning use cases like fraud detection and medical imaging analysis.

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.

Fibers are bendable and can therefore produce novel-shaped electronic devices. But their small diameters and high aspect ratios mean fibers must be extremely long to meet the energy demands of portable electronic systems.

Having no upper limit to fiber length opens a range of applications. The rechargeable battery can be woven to power wearable electronics and small robots.

Awards & Honors

Fellow, The Minerals, Metals & Materials Society
Fellow, American Association for the Advancement of Science
Fellow, Materials Research Society
Fellow, American Physical Society
Presidential Career Award for Scientists & Engineers