Bioinspired High-Sensitivity Temperature Sensor for Rapid and Autonomous Early Warning of Abnormal High Temperatures

Area of Science:

• Materials Science
• Biomimetics
• Sensor Technology

Background:

• Advancements in wearable technology necessitate flexible temperature sensors capable of detecting subtle thermal changes and responding to dangerous heat levels.
• Existing sensors often lack the dual capability for high-resolution detection and independent thermal alerts.
• Nature provides inspiration, such as scorpion slit sensilla sensitivity and gentian flower petal-opening responses to heat.

Purpose of the Study:

• To develop a flexible, bioinspired temperature sensor with high-resolution detection and self-triggered thermal alerts.
• To integrate natural design principles (scorpion sensilla, gentian flowers) into a functional sensor.
• To address the growing need for advanced temperature monitoring in wearable devices and safety systems.

Main Methods:

• Designed a bilayer heterogeneous architecture sensor using poly(ethylene oxide) (PEO)-graphene ink and a crack-based polylactic acid (PLA) layer.
• Utilized the PEO-graphene layer for sensitive detection in the low-temperature range (30-40 °C).
• Employed the cracked PLA layer, leveraging thermal bending and tunneling effects, for high-temperature range operation (40-70 °C).

Main Results:

• The PEO-graphene layer achieved high sensitivity up to 5.1% °C^-1 in the low-temperature range.
• The cracked PLA layer demonstrated sensitivity up to 0.146% °C^-1 in the high-temperature range.
• The integrated sensor system responded rapidly to temperature spikes, triggering a safety alert in 11.27 seconds.

Conclusions:

• The developed bioinspired sensor successfully integrates high-resolution temperature detection with self-triggered thermal alerts.
• The sensor's dual-range functionality and rapid response make it suitable for both conventional monitoring and abnormal high-temperature protection.
• This technology holds significant potential for applications in smart wearables, intelligent workplaces, and fire warning systems.