Mani Teja Vijjapu, an electrical engineering Ph.D. student, Khaled Nabil Salama and colleagues are said to have designed and fabricated an array of photoreceptors that detect the intensity of visible light through a change in electrical capacitance, mimicking the behaviour of the eye’s rod retina cells.
When the array was connected to an electronic CMOS-sensing circuit and a spiking neural network (a single-layer network with 100 output neurons), it was able to recognise 70 per cent of handwritten numbers.
“The ultimate goal of our research in this area is to develop efficient neuromorphic vision sensors to build efficient cameras for computer vision applications,” Salama said in a statement. “Existing systems use photodetectors that require power for their operation and thus consume a lot of energy, even on standby. In contrast, our proposed photoreceptors are capacitive devices that don’t consume static power for their operation.”
According to KAUST (King Abdullah University of Science & Technology, Saudi Arabia), the photoreceptor array is made by sandwiching a material with suitable optical and dielectric properties between a bottom aluminium electrode and a patterned top electrode of indium tin oxide to form a pixelated array of miniature light-sensitive metal-insulator-metal capacitors. The array is made on a thin substrate of polyimide so that it is flexible and can be curved, including to a hemispherical shape that mimics the human eye.
KAUST said the team used a hybrid material of perovskite (methylammonium lead bromide (MAPbBr3)) nanocrystals embedded in terpolymer polyvinylidene fluoride trifluoroethylene-chlorofluoroethylene (PVDF-TrFE-CEF). MAPbBr3 is a strong absorber of visible light, while PVDF-TrFE-CEF has a high dielectric constant.
“We chose hybrid perovskites because of their exceptional photoelectronic properties, such as excellent light absorption, long carrier lifetime and high carrier mobility,” said Vijjapu.
Tests with a 4x4 array and LED illumination of different visible colours indicate that the optical response of the array mimics the response of the human eye with a maximum sensitivity to green light. Importantly, the photoreceptors are also found to be highly stable, with no change in response after being stored for 129 weeks in ambient conditions.
Future plans for the team include building larger arrays of photoreceptors, optimising the interface circuit design and employing a multi-layered neural network to improve the accuracy of the recognition functionality.
The team's findings have been published in Nature Light: Science & Applications.