Opto‐Ferroelectric Coupling Enhanced α‐In <sub>2</sub> Se <sub>3</sub> Transistors With Light‐Controlled Mode Switchover

C Chengming Luo (Guangdong Provincial Key Laboratory of Chip and Integration Technology School of Electronic Science and Engineering (School of Microelectronics) South China Normal University Foshan People's Republic of China) W Wenjie Chen L Lei Zhao (School of Life Sciences, Key Laboratory of Pesticide and Chemical Biology of Ministry of Education, and Hubei Key Laboratory of Genetic Regulation and Integrative Biology, Central China Normal University) C Chenhao Xu Y Yanze Song Y Yue Wang Z Zhidong Pan T Tu Zhao Y Yan Li Y Yunxin Zhang Y Yujue Yang W Wenwu Li N Nengjie Huo

Abstract

ABSTRACT Neuromorphic computing is an ideal approach for achieving complex pattern recognition works; however, it is usually incompatible with digital logic processing units, limiting its application scope. Leveraging an opto‐ferroelectric coupling enhanced effect, we herein achieve the light‐controlled mode switchover between logic processing and neuromorphic computing in a ferroelectric transistor with α‐In 2 Se 3 /h‐BN as gate dielectrics and MoS 2 as channel. Under dark conditions, the transistor operates in digital logic mode with a high current on/off ratio of 10 9 , ultra‐low subthreshold swing (SS) of 33 mV/dec, and low leakage current of 5.6 × 10 −13 A, which is promising for logic processing applications. The inverter and NOR circuits with high noise margin and low power consumption were further implemented via interconnecting n‐ and p‐type transistors. Under light conditions, the ferroelectric polarization field of α‐In 2 Se 3 is significantly enhanced, leading to an enlarged hysteresis window (Δ V ) and switching the transistor into an optoelectronic synapse mode for neuromorphic computing, which can support image classification with an accuracy of up to 94.43% and a low energy consumption of 0.47 pJ/spike. This work provides an opto‐ferroelectric coupling‐enhanced transistor that addresses the incompatibility issue between digital logic and neuromorphic computing units, offering a new pathway for next‐generation computing devices.

Article Details

Volume / Issue Vol. 38, Issue 16
Published March 01, 2026
ISSN 0935-9648
Publisher Unknown Publisher

Journal Info

Advanced Materials

Unknown Publisher

ISSN: 0935-9648 Physical Sciences

Authors (13)

C

Chengming Luo

Guangdong Provincial Key Laboratory of Chip and Integration Technology School of Electronic Science and Engineering (School of Microelectronics) South China Normal University Foshan People's Republic of China

W

Wenjie Chen

L

Lei Zhao

School of Life Sciences, Key Laboratory of Pesticide and Chemical Biology of Ministry of Education, and Hubei Key Laboratory of Genetic Regulation and Integrative Biology, Central China Normal University

C

Chenhao Xu

Y

Yanze Song

Y

Yue Wang

Z

Zhidong Pan

T

Tu Zhao

Y

Yan Li

Y

Yunxin Zhang

Y

Yujue Yang

W

Wenwu Li

N

Nengjie Huo