Multifunctional Flexible Sensor with Bionic Micro‐Nano Hierarchical Structure for Dual‐Mode Pressure and Temperature Sensing

Why It Matters

The sensor’s combined high‑resolution pressure and temperature readouts open new possibilities for wearable health monitoring and tactile robotics, while its AI‑enabled gesture interface bridges human‑machine interaction gaps. Its scalable, flexible design positions it for rapid adoption in e‑skin and smart prosthetics.

Key Takeaways

• BMF sensor combines pressure and temperature detection
• Sensitivity: 986.51 kPa⁻¹ pressure, 9.891 µV·K⁻¹ temperature
• Response time 22 ms, range 0–200 kPa
• Hydrophobic micro‑nano hierarchy enables decoupled sensing
• Enables AI‑driven gesture recognition via wireless transmission

Pulse Analysis

Flexible electronics have moved from laboratory curiosities to core components of next‑generation wearables, electronic skin, and soft robotics. Traditional multifunctional sensors, however, often suffer from cross‑sensitivity, limited dynamic range, and slow response, which hampers reliable physiological monitoring. Researchers have turned to nature for solutions, copying the micro‑ and nano‑scale textures found on ant exoskeletons, spider silk, mosquito proboscises, and lotus leaves. These biological surfaces combine extreme hydrophobicity with mechanical compliance, offering a template for sensors that can operate in moist, dynamic environments without performance degradation.

The newly reported bionic multifunctional (BMF) sensor translates this bioinspiration into a practical device by integrating MXene‑coated melamine foam with a carbon‑nanotube/poly(vinylidene fluoride) nanofiber membrane. The resulting micro‑nano hierarchical architecture yields an unprecedented pressure sensitivity of 986.51 kPa⁻¹ across a 0–200 kPa span and a temperature coefficient of 9.891 µV·K⁻¹, while maintaining a rapid 22 ms response time. Its lotus‑leaf‑like water repellency prevents sweat or ambient moisture from short‑circuiting the active layers, allowing pressure and temperature signals to be decoupled and read independently with high fidelity.

Beyond raw performance, the BMF sensor demonstrates real‑world utility through a wireless, deep‑learning‑driven gesture‑recognition platform for robotic hands. By streaming dual‑mode data to an edge AI model, the system distinguishes subtle hand motions without physical contact, a capability valuable for sterile medical interfaces, augmented reality, and collaborative manufacturing. The flexible, scalable construction aligns with mass‑production techniques such as roll‑to‑roll printing, suggesting a clear path to commercial e‑skin, smart prosthetic, and health‑monitoring markets. As industries seek more nuanced tactile feedback, bioinspired, AI‑integrated sensors like this are poised to become foundational components of the Internet of Bodies.