Room-Temperature Wearable Chemiresistor Based on aFlexible Inorganic Photoactive Anatase–Rutile TiO₂/Yttria-Stabilized Zirconia Nanofiber Network

Wearable gas sensors offer remarkable advantages in terms of portability and real-time monitoring, rendering them highly promising for various applications such as environmental detection, health monitoring, and early disease diagnosis. However, the most widely used oxide semiconductor gas sensors encounter substantial challenges in achieving mechanical flexibility and room-temperature gas detection due to their inherent rigidity, brittleness, and reliance on high operating temperatures. Herein, an all-inorganic wearable oxide semiconductor gas sensor is fabricated by depositing the anatase/rutile TiO₂ (TiO₂-A/R) homojunction on a flexible yttria-stabilized zirconia (YSZ) nanofiber substrate using atomic layer deposition technology. The combination of the YSZ nanofiber and the ultrathin TiO₂ sensing layer (∼13 nm) endows the wearable sensor with tiny linear strains (0.55%) when subjected to a radius of curvature of 25 μm. As a result, the wearable inorganic YSZ/TiO₂-A/R sensor can be folded multiple times without fracturing and maintain a stable electrical connectivity during cyclic bending. Furthermore, the utilization of photoactive TiO₂ homojunctions allows the sensor to be activated by UV light and operated at room temperature. The efficient separation efficiency of photogenerated carriers, which stems from the interfacial electric field of TiO₂ homojunctions, significantly enhances the sensor’s response, leading to a low detection limit of 0.15 ppm for acetone. In addition, the wearable sensor was anchored on a mask and successfully utilized for the detection of a simulated breathing gas of diabetics; the real-time and stable response signals demonstrate its potential for noninvasive diabetes diagnosis. This study provides a valuable reference for the advancement of wearable room-temperature inorganic semiconductor gas sensors, offering valuable insights into their potential applications in disease diagnosis.