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

Area of Science:

• Materials Science
• Biomimetics
• Neuroscience

Background:

• Biological nervous systems offer a dynamic topological network architecture ideal for high-performance sensor design.
• Existing sensors lack the sensitivity and adaptability of biological systems.

Purpose of the Study:

• To construct a ZnO-based biomimetic pressure sensor mimicking neuronal structures.
• To investigate the synergistic modulation of quantum tunneling and contact resistance effects.
• To introduce an opto-mechano-electronic synergistic modulation mechanism for enhanced stability.

Main Methods:

• Hydrothermal self-assembly to create a ZnO micronetwork with 3D neuronal branching.
• Utilizing synapse-mimetic connections for modulation of electrical properties.
• Implementing ultraviolet light excitation for opto-mechano-electronic synergy.

Main Results:

• Achieved a triple-stage sensitivity gradient (S1=20.0 kPa⁻¹, S2=93.1 kPa⁻¹, S3=124.1 kPa⁻¹) over an ultrabroad pressure range (0.016–500 kPa).
• Enhanced sensor stability by 15.7% using opto-mechano-electronic modulation.
• Demonstrated high accuracy (98.3% for action recognition, 96.8% for Morse code conversion) in intelligent perception systems.

Conclusions:

• The biomimetic sensor offers a novel design paradigm for neuromorphic electronic devices.
• The study validates the potential of reconstructing biological topological networks for advanced sensing.
• This work provides a pathway for developing adaptive perception and human-machine interaction systems.