Synaptic Transistors Integrated With Triboelectric Nanogenerators for Artificial Perception and Neuromorphic Computing

ABSTRACT Bioinspired artificial perception systems (APS) are a crucial technical approach for future embodied intelligence, while mimicking perception with low power consumption, high integration, and matched transmission speed is the key element to achieve real‐time high‐efficiency APS. Recently, tribo‐transistors with a simple architecture have provided an innovative solution by directly converting mechanical stimuli into electrical signals, eliminating the need for external tactile sensors and thus improving integration and efficiency. In this review, we extend the discussion to opto–mechano–electric synergistic interactions, highlighting how triboelectric potentials can optically modulate synaptic transistors through field‐controlled charge transfer, exciton dynamics, and band engineering in low‐dimensional materials. We systematically summarize the working principles of triboelectric nanogenerators (TENGs) and tribo‐transistors, with a particular focus on photosensitive materials, optically transparent/active device architectures, and emerging scenarios such as optoelectronic neuromorphic vision systems and light‐triggered multisensory integration. Additionally, the current development prospects and challenges associated with tribo‐transistors APS are critically discussed, including new photonic functionalities such as triboelectric‐modulated photoluminescence and non‐Hermitian photonic sensing. This review aims to provide strategic insights into designing next‐generation APS and to establish a solid foundation for their future deployment in robotics and other advanced intelligent systems.

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Publication Details

Journal
Laser & Photonics Review
Published
2026-08-27
DOI
https://doi.org/10.1002/lpor.71789
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.00

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article

Synaptic Transistors Integrated With Triboelectric Nanogenerators for Artificial Perception and Neuromorphic Computing

Huipeng Chen, Hui Jing, Liying Jiang, 匡乐满 et al.
Laser & Photonics Review
Advanced Sensor and Energy Harvesting Materials
article

Synaptic Transistors Integrated With Triboelectric Nanogenerators for Artificial Perception and Neuromorphic Computing

Huipeng Chen, Hui Jing, Liying Jiang, 匡乐满, Linfeng Sun, Xu Yihang, Zhu Liu, Xiumei Wang, Zhang Manyu, Menghua Lang, Yaqian Liu
article en

Abstract

ABSTRACT Bioinspired artificial perception systems (APS) are a crucial technical approach for future embodied intelligence, while mimicking perception with low power consumption, high integration, and matched transmission speed is the key element to achieve real‐time high‐efficiency APS. Recently, tribo‐transistors with a simple architecture have provided an innovative solution by directly converting mechanical stimuli into electrical signals, eliminating the need for external tactile sensors and thus improving integration and efficiency. In this review, we extend the discussion to opto–mechano–electric synergistic interactions, highlighting how triboelectric potentials can optically modulate synaptic transistors through field‐controlled charge transfer, exciton dynamics, and band engineering in low‐dimensional materials. We systematically summarize the working principles of triboelectric nanogenerators (TENGs) and tribo‐transistors, with a particular focus on photosensitive materials, optically transparent/active device architectures, and emerging scenarios such as optoelectronic neuromorphic vision systems and light‐triggered multisensory integration. Additionally, the current development prospects and challenges associated with tribo‐transistors APS are critically discussed, including new photonic functionalities such as triboelectric‐modulated photoluminescence and non‐Hermitian photonic sensing. This review aims to provide strategic insights into designing next‐generation APS and to establish a solid foundation for their future deployment in robotics and other advanced intelligent systems.

Laser & Photonics Review
Anhui Agricultural University (CN), Zhengzhou University of Light Industry (CN), Ministry of Education (IR), Beijing Academy of Quantum Information Sciences (CN), Fuzhou University (CN)
National Natural Science Foundation of China, Science and Technology Innovation Talents in Universities of Henan Province
Affordable and clean energy
Openalex Percentile: Top 19%
Advanced Sensor and Energy Harvesting Materials
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