2D Piezo‐Ferro‐Opto‐Electronic Artificial Synapse for Bio‐Inspired Multimodal Sensory Integration

M Mengqi Wang D Decai Ouyang (State Key Laboratory of New Textile Materials and Advanced Processing, School of Materials Science and Engineering Huazhong University of Science and Technology Wuhan P. R. China) Y Yin Dai (1College of Medicine and Biological Information Engineering, Northeastern University, shenyang, China) D Da Huo W Wenke He (Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China 1 , Chengdu 611731,) B Bailing Song (School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan Hubei 430070 P. R. China) W Wenhua Hu (School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan Hubei 430070 P. R. China) M Menghao Wu (School of Physics, Huazhong University of Science and Technology 2 , Wuhan, Hubei 430074,) Y Yuan Li T Tianyou Zhai (State Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering)

Abstract

AbstractMultimodal sensory integration is vital for the evolution of artificial intelligence, yet current approaches often rely on physically connecting distinct sensing units (such as visual and tactile devices) through external circuits, leading to data transmission delays and information loss. Here, a groundbreaking paradigm is demonstrated for integrating visual‐tactile fusion perception in one device with a single functional material. This is achieved by developing an unprecedented 2D Piezo‐Ferro‐Opto‐Electronic (PFOE) Artificial Synapse, which combines the comprehensive ferroelectricity (for synaptic behaviors), piezoelectricity (for tactile modulation), and optoelectronic responsiveness (for visual detection) of strained 2D NbOI2. Under the synergistic influence of light and strain, the device exhibits remarkable persistent photoconductivity (PPC), a notable increase in paired‐pulse facilitation (PPF) index (from 116% to 180%), and a reduction in the power exponent of the sublinear power‐law fitting photocurrent curve (from 0.797 to 0.376). These features enhance the clarity and recognition of fingerprint images that integrate visual and tactile information. The work provides a robust foundation for integrating multisensory capabilities into advanced human‐machine interfaces and artificial intelligence systems, marking a significant leap forward in the development of multifunctional neuromorphic devices.

Article Details

Volume / Issue Vol. 37, Issue 24
Published June 01, 2025
ISSN 0935-9648
Publisher Unknown Publisher

Journal Info

Advanced Materials

Unknown Publisher

ISSN: 0935-9648 Physical Sciences

Authors (10)

M

Mengqi Wang

D

Decai Ouyang

State Key Laboratory of New Textile Materials and Advanced Processing, School of Materials Science and Engineering Huazhong University of Science and Technology Wuhan P. R. China

Y

Yin Dai

1College of Medicine and Biological Information Engineering, Northeastern University, shenyang, China

D

Da Huo

W

Wenke He

Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China 1 , Chengdu 611731,

B

Bailing Song

School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan Hubei 430070 P. R. China

W

Wenhua Hu

School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan Hubei 430070 P. R. China

M

Menghao Wu

School of Physics, Huazhong University of Science and Technology 2 , Wuhan, Hubei 430074,

Y

Yuan Li

T

Tianyou Zhai

State Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering