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Updated: Sep 8, 2026

Fabrication of Flexible Image Sensor Based on Lateral NIPIN Phototransistors
Published on: June 23, 2018
Gate-Tunable Polarity-Reconfigurable Photovoltaic Response With Dual Linearity in NbS3/WSe2 Heterostructures for
Jidong Liu1, Jianxiong Xie1, Qiaoyan Hao1
1State Key Laboratory of Radio Frequency Heterogeneous Integration, International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology of Ministry of Education, Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, China.
Abstract:
Reconfigurable optoelectronic image sensors capable of in-sensor computing are promising for energy-efficient edge visual perception. Self-powered photovoltaic operation further reduces the power demand of image sensing and processing. However, it remains challenging to achieve a continuously gate-tunable self-powered photovoltaic response that combines reversible polarity with linear weight programmability. Here, we demonstrate a gate-tunable photovoltaic detector based on an NbS3/WSe2 van der Waals heterostructure. Owing to the ambipolar transport of WSe2 and the distinct electrostatic responses of the two constituent materials, gate voltage continuously modulates the interfacial band alignment and reversibly switches the built-in electric field at the heterointerface. Consequently, the device exhibits gate-controlled positive and negative photovoltaic responses. The short-circuit photocurrent scales linearly with incident power density, while the short-circuit photoresponsivity varies linearly with gate voltage over a broad programming window. This dual linearity allows the photoresponsivity to function as a programmable analog weight for in-sensor convolution. As a proof of concept, several image convolution kernels are implemented for in-sensor image processing, and the experimentally obtained outputs agree well with algorithmic simulations. This work provides a promising device-level building block for reconfigurable and energy-efficient vision sensors for edge computing.

