ORLANDO, Fla., Feb. 20, 2020 — University of Central Florida (UCF) researchers have taken a step toward developing neuromorphic computers — computers that mimic neurobiological architectures present in the human nervous system — by demonstrating how to create a nanoscale device that can mimic the neural pathways of brain cells used for human vision. “Our group created a single device that mimics the eye and the brain function together,” professor Tania Roy said. “Our device can observe the image and recognize it on the spot.”
The researchers grew perovskite quantum dots (PQDs) directly on 2D, atomic-thick nanomaterial (graphene). They used the graphene-PQD superstructure to develop ultrathin phototransistors and photonic synapses.
The graphene-PQD superstructure synchronized efficient charge generation and transport on the single platform. The PQDs captured light, converted the light to electric charges, and transferred the charges directly to the graphene, all in one step. The entire process took place on an extremely thin film, about one ten-thousandths of the thickness of a human hair.
The graphene-PQD phototransistors exhibited excellent responsivity, the team said. Moreover, the light-assisted memory effect of these superstructures enabled photonic synaptic behavior.
To test their device’s ability to see objects through neuromorphic computing, the researchers used it in facial recognition experiments assisted by machine learning.
“The facial recognition experiment was a preliminary test to check our optoelectronic neuromorphic computing,” professor Jayan Thomas said. “Since our device mimics vision-related brain cells, facial recognition is one of the most important tests for our neuromorphic building block.”
They found that their device was able to successfully recognize the portraits of four different people. “Because of the nature of the superstructure, it shows a light-assisted memory effect,” Basudev Pradhan, assistant professor at the Central University of Jharkhand in India, said. “This is similar to humans’ vision-related brain cells. The optoelectronic synapses we developed are highly relevant for brain-inspired, neuromorphic computing.”
The researchers hope that the graphene-PQD superstructures will open new directions in the development of highly efficient optoelectronic devices. Potential applications include drone-assisted rescues and defense. “Such features can also be used for aiding the vision of soldiers on the battlefield,” researcher Sonali Das said. “Further, our device can sense, detect, and reconstruct an image along with extremely low power consumption, which makes it capable for long-term deployment in field applications.”
The team plans to continue its collaboration to refine the device, including using it to develop a circuit-level system.
The research was published in Science Advances (www.doi.org/10.1126/sciadv.aay5225).