Curved neuromorphic image sensor array using a MoS2-organic heterostructure inspired by the human visual recognition system

TLDR

Conventional imaging systems rely on extensive data storage, pre‑processing, and complex optics, whereas human vision achieves efficient recognition with minimal hardware. Inspired by human vision, we propose a curved neuromorphic image sensor array that performs on‑chip data pre‑processing to streamline image acquisition. The array is built from a MoS₂/organic heterostructure that exhibits photon‑triggered synaptic plasticity through quasi‑linear photocurrent generation and prolonged decay due to charge trapping. When coupled with a plano‑convex lens, the sensor produces pre‑processed images from noisy inputs without redundant storage or complex optics, markedly improving machine‑vision efficiency.

Abstract

Abstract Conventional imaging and recognition systems require an extensive amount of data storage, pre-processing, and chip-to-chip communications as well as aberration-proof light focusing with multiple lenses for recognizing an object from massive optical inputs. This is because separate chips ( i . e ., flat image sensor array, memory device, and CPU) in conjunction with complicated optics should capture, store, and process massive image information independently. In contrast, human vision employs a highly efficient imaging and recognition process. Here, inspired by the human visual recognition system, we present a novel imaging device for efficient image acquisition and data pre-processing by conferring the neuromorphic data processing function on a curved image sensor array. The curved neuromorphic image sensor array is based on a heterostructure of MoS 2 and poly(1,3,5-trimethyl-1,3,5-trivinyl cyclotrisiloxane). The curved neuromorphic image sensor array features photon-triggered synaptic plasticity owing to its quasi-linear time-dependent photocurrent generation and prolonged photocurrent decay, originated from charge trapping in the MoS 2 -organic vertical stack. The curved neuromorphic image sensor array integrated with a plano-convex lens derives a pre-processed image from a set of noisy optical inputs without redundant data storage, processing, and communications as well as without complex optics. The proposed imaging device can substantially improve efficiency of the image acquisition and recognition process, a step forward to the next generation machine vision.