Adaptive self-powered photodetection and neuromorphic computing in a CuCrP2S6 ionotronic device

Abstract

In-sensor computing devices integrating sensing and processing functions are emerging as key enablers for next-generation artificial vision systems. Their development critically depends on identifying materials capable of mimicking the adaptive, multimodal behavior of biological synapses. Here, we demonstrate CuCrP₂S₆ (CCPS), a two-dimensional metal thiophosphate, as an optoelectronic neuromorphic material that simultaneously supports photodetection and synaptic plasticity. A CCPS photodetector exhibits both strong photoconductive behavior and a self-powered photoresponse at zero bias through directional ion migration. The vertical device architecture exhibits an intrinsic photoresponsivity of 420 mA W⁻¹ and a specific detectivity of up to 3.5 × 10¹⁰ Jones. Crucially, both the magnitude and polarity of the photovoltaic current can be reversibly tuned by controlling ionic migration, mimicking the long-term potentiation and depression. A CCPS-based photonic synapse network achieves 89.8% image recognition accuracy on the Fashion-MNIST dataset, approaching the full-precision benchmark. Furthermore, a 3 × 3 CCPS photodetector array enables a programmable spatial light response, facilitating in-sensor image preprocessing such as edge enhancement. This work highlights CCPS as a multifunctional material platform for integrated perception–computation electronics and paves the way for intelligent, on-chip visual processing systems.