Functional Inorganic Materials and Devices
- Jie Cheng
Jie Cheng
The State Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University, Changsha 410073, China
More by Jie Cheng
- Xinyu Ouyang
Xinyu Ouyang
The State Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University, Changsha 410073, China
More by Xinyu Ouyang
- Xin Tang
Xin Tang
The State Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University, Changsha 410073, China
More by Xin Tang
- Bingdong Qin
Bingdong Qin
The State Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University, Changsha 410073, China
More by Bingdong Qin
- Shu Liu
Shu Liu
The State Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University, Changsha 410073, China
More by Shu Liu
- Hu Chen
Hu Chen
College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China
More by Hu Chen
- Bing Song
Bing Song
College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China
More by Bing Song
- Yu Zheng*
Yu Zheng
The State Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University, Changsha 410073, China
*Email: [emailprotected]
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ACS Applied Materials & Interfaces
Cite this: ACS Appl. Mater. Interfaces 2025, XXXX, XXX, XXX-XXX
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https://pubs.acs.org/doi/10.1021/acsami.5c01496
Published April 16, 2025
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Recently, the growing demand for data-centric applications has significantly accelerated progress to overcome the “memory wall” caused by the separation of image sensing, memory, and computing units. However, despite advancements in novel devices driving the development of the in-sensor computing paradigm, achieving seamless integration of optical sensing, storage, and image processing within a single device remains challenging. This study demonstrates an in-sensor computing architecture using a ferroelectric-defined reconfigurable α-In2Se3 phototransistor. The three polarization states of the device exhibit a linear and distinguishable photoresponse, with a maximum photoresponse current difference of 2.17 × 10–6 A and a retention time exceeding 500 s. The nonvolatile weight and synaptic properties are programmed by external electrical stimulation, enabling 112 distinct conductance states with a nonlinearity of 0.12. Additionally, the device supports efficient optical writing, electrical erasing, optoelectronic logic, and decoding via combined optoelectronic control. In-sensor computation for image edge detection is simulated by embedding a nonvolatile Prewitt convolution kernel into a 3 × 3 device array. The integrated structure and array design highlight the strong potential of 2D ferroelectric semiconductors for in-sensor computing, providing a promising platform for next-generation multifunctional artificial vision systems.
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© 2025 American Chemical Society
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- Circuits
- Electrical conductivity
- Light
- Optoelectronics
- Polarization
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ACS Applied Materials & Interfaces
Cite this: ACS Appl. Mater. Interfaces 2025, XXXX, XXX, XXX-XXX
Click to copy citationCitation copied!
Published April 16, 2025
Publication History
Received
Accepted
Revised
Published
online
© 2025 American Chemical Society
Request reuse permissions
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