Researchers develop graphene-based synaptic transistors for neuromorphic computing

Researchers from The University of Texas at Austin and Sandia National Laboratories have developed graphene-based synaptic transistors for brain-like computers. These transistors are similar to synapses in the brain, that connect neurons to each other.

"Computers that think like brains can do so much more than today's devices," said Jean Anne Incorvia, an assistant professor at The University of Texas at Austin and the lead author on the paper. "And by mimicking synapses, we can teach these devices to learn on the fly, without requiring huge training methods that take up so much power."

In their work, the team used a combination of graphene and nafion, a polymer membrane material, for the backbone of the synaptic transistor. Together, these materials demonstrated key synaptic-like behaviors — most importantly, the ability for the pathways to strengthen over time as they are used more often, a type of neural muscle memory. In computing, this means that devices will be able to get better at tasks like recognizing and interpreting images over time and do it faster.

Another important finding is that these transistors are biocompatible, which means they can interact with living cells and tissue. That is key for potential applications in medical devices that come into contact with the human body. Most materials used for these early brain-like devices are toxic, so they would not be able to contact living cells in any way.


Biocompatibility, flexibility, and softness of our artificial synapses is essential, said Dmitry Kireev, a post-doctoral researcher who co-led the project. In the future, we envision their direct integration with the human brain, paving the way for futuristic brain prosthesis.

While neuromorphic platforms are starting to become more common, with leading chipmakers either producing neuromorphic chips or are in the process of developing them, current chip materials still place limitations on what neuromorphic devices can do, so researchers are working to find the perfect materials for soft brain-like computers.

"It's still a big open space when it comes to materials; it hasn't been narrowed down to the next big solution to try," Incorvia said. "And it might not be narrowed down to just one solution, with different materials making more sense for different applications."

Posted: Aug 15,2022 by Roni Peleg