Photoactive Electro-Controlled Visual Perception Memory for Emulating Synaptic Metaplasticity and Hebbian Learning

In bionic technology, it has become an innovative process imitating the functionality and structuralism of human biological systems to exploit advanced artificial intelligent machines. Bionics plays a significant role in environmental protection, especially for its low energy loss. By fusing the concept of receptor-like sensing component and synapse-like memory, the photoactive electro-controlled optical sensory memory (PE-SM) is proposed and realized in a single device, which endows a simple methodology of reducing power consumption by photoactive electro-control. The PE-SM is the system built with the stacked atomically thick materials, in which rhenium diselenide serves as a robust photosensor, hexagonal boron nitride serves as a tunneling dielectric, and graphene serves as a charge-storage layer. With the features of the PE-SM, it performs synaptic metaplasticities under optical spikes. In addition, a simulated spiking neural network composed of 24 x 24 PE-SMs is further presented in an unsupervised machine learning environment, performing image recognition via the Hebbian rule. The PE-SM not only improves the neuromorphic computing efficiency but also simplifies the circuit-size structure. Eventually, the concept of photoactive electro-control can extend to other photosensitive 2D materials and provide a new approach of constructing either visual perception memory or photonic synaptic devices.

Automated summary

The PE-SM is an innovative technology that combines receptor-like sensing components and synapse-like memory to reduce energy consumption. Constructed with stacked atomically thick materials, the PE-SM enables synaptic metaplasticities and image recognition in an unsupervised machine learning environment.