Ge‐Based Visible‐Infrared Bipolar Floating‐Gate Phototransistor for Broad‐Spectrum Retinal Bionics
Bipolar cells play a crucial role in perceiving, transmitting, and processing visual information by effectively segregating visual signals into ON and OFF pathways. However, conventional visual signals are predominantly confined to the visible (Vis) wavelength range, which significantly restricts the potential applications of bipolar cells. Here, a germanium (Ge)-based floating-gate tungsten diselenide (WSe<sub>2</sub>) phototransistor capable of mimicking broad-spectrum bipolar cell functionality is proposed, which extend the utility from artificial retinal systems to advanced image processing applications. The floating gate of the phototransistor can non-volatilely storage electrons/holes, modulating the WSe<sub>2</sub> channel to exhibit bipolar characteristics. Under distinct bottom gate voltage pulse modulations, the bipolar WSe<sub>2</sub> channel interfaces with multilayer graphene (MLG) to form Schottky built-in electric fields with opposing directions, enabling bipolar photoresponse under visible light illumination. Meanwhile, by leveraging the near-infrared (NIR) light absorption of Ge and the photogating effect, the device demonstrates NIR bipolar photoresponse. Based on the unique dual-band bipolar photoresponse characteristics of this single phototransistor, the neural biological functions of bipolar cells in the human retina are successfully emulated, and an image sharpening processing based on convolutional operation is demonstrated. This advancement significantly enhances the potential of visual bionic chips for applications in vehicles or robots.
Authors
- Zhangming Zhu (ORCID: https://orcid.org/0000-0002-7764-1928)
- Liming Wang (ORCID: https://orcid.org/0000-0001-5751-5126)
- Qiancui Zhang
- Tian Miao (ORCID: https://orcid.org/0000-0001-7889-6490)
- Huiyong Hu
- Ningning Zhang (ORCID: https://orcid.org/0000-0002-5507-7713)
- Yichi Zhang (ORCID: https://orcid.org/0000-0001-8664-586X)
- Liu Xie
Institutions
- Xidian University (CN)
Publication Details
- Journal
- Advanced Science
- Published
- 2025-09-19
- DOI
- https://doi.org/10.1002/advs.202512649
- Citations
- 2
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 1.46
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Servier
- National Key Research and Development Program of China