Highly sensitive flexible dielectric-response-based taste sensor for generic liquid identification

Artificial taste sensors mimicking human tongue enables a non-destructive, rapid, and objective method for taste assessment, and the integration of multiple sensing units to fully emulate human gustatory system remains challenge. Here, we present a dielectric-response-based taste (DRT) sensor with a facile structure for generic liquid identification. The representative tastants of the five basic tastes have been identified with a wide range (10 mu M-100 mM), a low limit of the detection (5 mu M), and long-term stability (>30 d). Moreover, mixtures of tastants can be distinguished by combining the potential and conductance measurement modes of the DRT sensor. An accuracy of 98.98% has been achieved on recognizing the types of six different beverages by the proposed sensor with the assistance of machine learning. The DRT sensor based on the idea of direct acquiring dielectric responses shows excellent performances in transcending human gustatory senses, providing an efficient, stable and low-cost method for applications in food industry, pharmaceutics, and environment monitoring.