Bioinspired Neuromorphic Pressure Sensor with Ultra-Broad Range and High Sensitivity for Intelligent Flexible Electronics

The dynamic topological network architecture evolved over billions of years in biological nervous systems and provides an ideal paradigm for designing high-performance biomimetic sensors. Here, a ZnO composed micronetwork with three-dimensional neuronal branching structure, as the core and sensitive unit of a pressure sensor, is constructed by hydrothermal self-assembly. Its synapse-mimetic connection mechanism enables synergistic modulation of quantum tunneling and contact resistance effects. This biomimetic sensor exhibits a unique triple-stage sensitivity gradient (<i>S</i><sub>1</sub> = 20.0 kPa<sup>-1</sup>, <i>S</i><sub>2</sub> = 93.1 kPa<sup>-1</sup>, <i>S</i><sub>3</sub> = 124.1 kPa<sup>-1</sup>) across an ultrabroad pressure range (0.016-500 kPa). Innovatively, an opto-mechano-electronic synergistic modulation mechanism was introduced: photogenerated carriers excited by 365 nm ultraviolet light effectively compensate the interfacial recombination current loss, enhancing the sensor stability by 15.7% during prolonged pressure testing. The sensor exhibits excellent performance in applications including complex-curvature adaptive perception, human motion monitoring, and human-machine interaction. An intelligent perception system incorporating machine learning algorithms achieved accuracy of 98.3% in human action recognition and real-time accuracy of 96.8% in Morse code conversion, validating its potential for neuromorphic perception. This study, from the perspectives of biological topological network reconstruction and multiphysic fields coupling, provides an innovative design paradigm and technical pathway for developing neuromorphic electronic devices.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2026-02-16
DOI
https://doi.org/10.1021/acsami.5c24104
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
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article

Bioinspired Neuromorphic Pressure Sensor with Ultra-Broad Range and High Sensitivity for Intelligent Flexible Electronics

Fuling Yang, Zijun Ning, Sicheng Zong, Jinbao Yuan et al.
ACS Applied Materials & Interfaces
Advanced Sensor and Energy Harvesting Materials
article

Bioinspired Neuromorphic Pressure Sensor with Ultra-Broad Range and High Sensitivity for Intelligent Flexible Electronics

Fuling Yang, Zijun Ning, Sicheng Zong, Jinbao Yuan, J. Wang, Yan Li, Du Guo, Yuanyuan Qu
article en

Abstract

The dynamic topological network architecture evolved over billions of years in biological nervous systems and provides an ideal paradigm for designing high-performance biomimetic sensors. Here, a ZnO composed micronetwork with three-dimensional neuronal branching structure, as the core and sensitive unit of a pressure sensor, is constructed by hydrothermal self-assembly. Its synapse-mimetic connection mechanism enables synergistic modulation of quantum tunneling and contact resistance effects. This biomimetic sensor exhibits a unique triple-stage sensitivity gradient (<i>S</i><sub>1</sub> = 20.0 kPa<sup>-1</sup>, <i>S</i><sub>2</sub> = 93.1 kPa<sup>-1</sup>, <i>S</i><sub>3</sub> = 124.1 kPa<sup>-1</sup>) across an ultrabroad pressure range (0.016-500 kPa). Innovatively, an opto-mechano-electronic synergistic modulation mechanism was introduced: photogenerated carriers excited by 365 nm ultraviolet light effectively compensate the interfacial recombination current loss, enhancing the sensor stability by 15.7% during prolonged pressure testing. The sensor exhibits excellent performance in applications including complex-curvature adaptive perception, human motion monitoring, and human-machine interaction. An intelligent perception system incorporating machine learning algorithms achieved accuracy of 98.3% in human action recognition and real-time accuracy of 96.8% in Morse code conversion, validating its potential for neuromorphic perception. This study, from the perspectives of biological topological network reconstruction and multiphysic fields coupling, provides an innovative design paradigm and technical pathway for developing neuromorphic electronic devices.

ACS Applied Materials & InterfacesVol. 18(7)
China University of Mining and Technology (CN), Robotics Research (United States) (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 54%
Advanced Sensor and Energy Harvesting Materials
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