A highly sensitive and flexible gas sensor that can detect a wide range of chemicals is crucial for wearable applications. However, conventional single resistance-based flexible sensors face challenges in maintaining chemical sensitivity under mechanical stress and can be affected by interfering gases. This study presents a versatile approach for fabricating a micropyramidal flexible ion gel sensor, which accomplishes sub-ppm sensitivity (<80 ppb) at room temperature and discrimination capability between various analytes, including toluene, isobutylene, ammonia, ethanol, and humidity. The discrimination accuracy of our flexible sensor is as high as 95.86%, enhanced by using machine learning-based algorithms. Moreover, its sensing capability remains stable with only a 2.09% change from the flat state to a 6.5 mm bending radius, further amplifying its universal usage for wearable chemical sensing. Therefore, we envision that a micropyramidal flexible ion gel sensor platform assisted by machine learning-based algorithms will provide a new strategy toward next-generation wearable sensing technology.
Keywords: VOCs sensor; flexible; ion gel; machine learning; strain compensation.