Neuromorphic computing is the use of the human brain as design inspiration for computer systems, and has been steadily gaining interest since the 1980’s. Its potential to improve both speed and energy efficiency in computing, and subsequently supercomputing, make neuromorphic computing a thriving area of interest.
While not attempting to directly copy the human brain, neuromorphic computing draws inspiration from neurons and synapses to develop new means of computation and information transfer. Innovation is an important part of the field of neuromorphic computing, and Francisco Barrera, associate professor of Biochemistry & Cellular and Molecular Biology, is bringing a new approach to chip development.
Historically Barrera’s work has focused on the plasma membrane, a protective barrier between individual cells and their external environments, which also regulate cell signaling or communication between cells. For this StART project, Barrera is using his expertise in collaboration with Pat Collier, staff researcher at ORNL.
“The Collier laboratory is working to recreate how neurons work using a system called droplet interface bilayer,” said Barrera. In a droplet interface bilayer, DIB, system there are small membranes that closely mimic the membranes of neurons. When connected, these membranes have been shown to do some promising computing.
Barrera’s team’s work could improve the function and connectivity of these membranes. They have designed a peptide that, when added into the membranes, canb change how currents move across the membranes, which is important for communication.
“What I think is very exciting is that I believe we can make an important contribution, because we try to understand, at a very deep level, how our peptides interact with lipids in the membrane,” said Barrera. “This is the kind of basic knowledge that allows you to understand a system and predict how it will respond.”
Barrera hopes the discoveries made with this StART project will ultimately lead to increased power and flexibility in chips for neuromorphic computing.