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Published on: May 13, 2020
Photo-Induced Valence Changed Memristor Based on WO3 and Polyvinyl Alcohol Nanocomposites for In-Sensor Reservoir
Junchao Zhang1, Zhuangzhuang Li1, Yankun Cheng1
1State Key Laboratory of Integrated Optoelectronics, Key Laboratory for UV Light-Emitting Materials and Technology of Ministry of Education, School of Physics Northeast Normal University, Changchun, China.
Abstract:
In-sensor reservoir computing based on optoelectronic synapses is a promising candidate to develop high-efficiency neuromorphic vision, owing to their ability to directly sensing and processing optical signals. Here, a photo-induced valence change memristor based on WO3 nanoparticles and polyvinyl alcohol (WO3@PVA) is developed, in which PVA functions as a proton donor, effectively enhancing the photocurrent response and photocurrent relaxation time of the device. Several fundamental synaptic functions have been emulated by utilizing ultraviolet light stimulation, including excitatory postsynaptic currents (EPSCs), short-term/long-term synaptic plasticity (STP/LTP) and learning-experience behaviors. In situ x-ray photoelectron spectroscopy analysis confirms that the photo-induced valence changed in tungsten oxide is the intrinsic mechanism underlying memristive switching. Furthermore, an in-sensor reservoir computing system was constructed by leveraging the photo-induced nonlinear dynamics and short-term memory characteristics of device, enabling static image classification and motion recognition with high precision. Our work provides a feasible pathway toward the development of optoelectronic synapse devices for application in high-efficiency neuromorphic visual systems.

