Emerging triboelectric nanogenerator-based neuromorphic electronics: From self-powered sensing to bioinspired synapses

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Authors: Shang-Ming Li, Xin-Gui Tang, Chen Yi-cong, Dan Zhang, Qi-Jun Sun, Yan-Ping Jiang
Cited by: 6
References: 137

Abstract

Triboelectric nanogenerators (TENGs) provide self-powered interfaces that convert biomechanical motions and environmental stimuli into electrical signals, offering new opportunities for energy-autonomous neuromorphic electronics. This review summarizes recent advances in TENG-based neuromorphic systems from three aspects: electrical signal generation, bioinspired sensory encoding, and synaptic information processing. The working mechanisms and electrical output characteristics of TENGs are first discussed, including voltage/current pulse generation, charge transfer, load-dependent power output, signal stability, and mechanical-input-dependent modulation. Representative material systems and device architectures are then reviewed, with emphasis on flexible polymers, biocompatible composites, ferroelectric materials, memristive devices, and heterojunction transistors. Recent applications are further categorized into self-powered auditory and tactile sensors, wearable health monitoring devices, AI-assisted sensing platforms, and triboelectric artificial synapses. This review establishes a device-to-system framework linking TENG electrical outputs with sensory encoding, synaptic modulation, and neuromorphic information processing. Finally, key challenges and future directions are discussed, including output stability, signal matching, device integration, durability, biocompatibility, and standardized evaluation metrics.

Fields of Study & Subjects

Advanced Sensor and Energy Harvesting Materials Conducting polymers and applications Supercapacitor Materials and Fabrication

Publication details

Journal / source
Results in Engineering
Publisher
Elsevier BV
Volume
30
Pages
111295–111295
Publication date
28 May 2026
Language
EN