Neuromorphic visual systems emulating biological retina functionalities have enormous potential for in-sensor computing, with prospects of making artificial intelligence ubiquitous. Conventionally, visual information is captured by an image sensor, stored by memory units, and eventually processed by the machine learning algorithm. Here, we present an optoelectronic synapse device with multifunctional integration of all the processes required for real time object identification.
View Article and Find Full Text PDFOptoelectronic synapses combine the functionalities of a non-volatile memory and photodetection in the same device, paving the path for the realization of artificial retina systems which can capture, pre-process, and identify images on the same platform. Graphene/TaO/graphene phototransistor exhibits synapse characteristics when visible electromagnetic radiation of wavelength 405 nm illuminates the device. The photocurrent is retained after light withdrawal when positive gate voltage is applied to the device.
View Article and Find Full Text PDFBrain-inspired computing enabled by memristors has gained prominence over the years due to the nanoscale footprint and reduced complexity for implementing synapses and neurons. The demonstration of complex neuromorphic circuits using conventional materials systems has been limited by high cycle-to-cycle and device-to-device variability. Two-dimensional (2D) materials have been used to realize transparent, flexible, ultra-thin memristive synapses for neuromorphic computing, but with limited knowledge on the statistical variation of devices.
View Article and Find Full Text PDFActin plays critical roles in various cellular functions, including cell morphogenesis, differentiation, and movement. The assembly of actin monomers into double-helical filaments is regulated in surrounding microenvironments. Graphene is an attractive nanomaterial that has been used in various biomaterial applications, such as drug delivery cargo and scaffold for cells, due to its unique physical and chemical properties.
View Article and Find Full Text PDFOptical data sensing, processing and visual memory are fundamental requirements for artificial intelligence and robotics with autonomous navigation. Traditionally, imaging has been kept separate from the pattern recognition circuitry. Optoelectronic synapses hold the special potential of integrating these two fields into a single layer, where a single device can record optical data, convert it into a conductance state and store it for learning and pattern recognition, similar to the optic nerve in human eye.
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