Graphene/MoS2−xOx/graphene photomemristor with tunable non-volatile responsivities for neuromorphic vision processing

TLDR

AI machine vision relies on separate sensing, computing, and storage units, causing high power consumption and latency due to frequent data movement. The study proposes offloading memory and computation to sensor elements that simultaneously perceive and process optical signals. A two‑terminal non‑volatile photomemristor couples photoexcited carriers with oxygen‑related ions, enabling responsivity modulation by charge or photon flux and storing the state, producing a displaced pinched hysteresis in its I‑V curve. These photomemristors realize computationally complete logic with photoresponse‑stateful operations, serving as both logic gate and memory, and their polarity reversal offers promising in‑memory sensing, feature extraction, and image recognition for neuromorphic vision.

Abstract

Conventional artificial intelligence (AI) machine vision technology, based on the von Neumann architecture, uses separate sensing, computing, and storage units to process huge amounts of vision data generated in sensory terminals. The frequent movement of redundant data between sensors, processors and memory, however, results in high-power consumption and latency. A more efficient approach is to offload some of the memory and computational tasks to sensor elements that can perceive and process the optical signal simultaneously. Here, we proposed a non-volatile photomemristor, in which the reconfigurable responsivity can be modulated by the charge and/or photon flux through it and further stored in the device. The non-volatile photomemristor has a simple two-terminal architecture, in which photoexcited carriers and oxygen-related ions are coupled, leading to a displaced and pinched hysteresis in the current-voltage characteristics. For the first time, non-volatile photomemristors implement computationally complete logic with photoresponse-stateful operations, for which the same photomemristor serves as both a logic gate and memory, using photoresponse as a physical state variable instead of light, voltage and memresistance. The polarity reversal of photomemristors shows great potential for in-memory sensing and computing with feature extraction and image recognition for neuromorphic vision.