Perovskite oxide based transparent neuromorphic photoelectric memristor for artificial ocular system

The emergence of photoelectric memristors has opened up new opportunities for the research community to realize the neuro-synaptic functionalities of photoelectric systems. Neuromorphic photoelectric memristors (NPMs) can directly respond to non-contact photonic signals while possessing the desirable features of high bandwidth, zero latency, and low crosstalk. With their capability to integrate the sensing, memory, and computing features, they can mimic the human vision system. Here, we propose a perovskite oxide (ABO3)-based NPM, where the active medium is comprised of oxygen rich and oxygen deficient layers of barium strontium titanate. Along with the analog-type resistive switching behavior, the device current modulation also enables the imitation of long term-potentiation/depression behaviors of the human brain. The designed convolutional neural network model achieves high accuracy even when tested with the damaged (noisy) face images of the Olivetti Research Laboratory dataset. The photo-excitation and photo-inhibition phenomena of NPM are observed under 405 and 633 nm illumination, respectively, and further utilized to realize the spike-intensity, spike-width, spike-rate, and spike-number dependent synaptic plasticity behaviors. These findings significantly inspire future research in the field of perovskite oxide based transparent photoelectric synaptic resistive switching memory devices.