Conformal Temperature/Impedance Sensing Patch Based on Graphene Materials for Nondestructive Detection of Fish Freshness.

Abstract

Rapid nondestructive detection of fish freshness is essential to ensure food safety and nutrition. In this study, we demonstrate a conformal temperature/impedance sensing patch for temperature monitoring, as well as freshness classification during fish storage. The optimization of the flexible laser-induced graphene electrodes is studied based on both simulation and experimental validation, and dimensional accuracy of 5‰ and high impedance reproducibility are obtained. A laser-assisted thermal reduction technology is innovatively introduced to directly form a reduced graphene oxide-based temperature-sensitive layer on the surface of a flexible substrate. The comprehensive performance is superior to that of most reported temperature-sensitive devices based on graphene materials. As an application demonstration, the fabricated flexible dual-parameter sensing patch is conformed to the surface of a refrigerated fish. The patch demonstrates the ability to accurately sense low temperatures in a continuous 120 min monitoring, accompanied by no interference from high humidity. Meanwhile, the collected impedance data are imported into the support vector machine model to obtain a freshness classification accuracy of 93.07%. The conformal patch integrated with crosstalk-free dual functions costs less than $1 and supports free customization, providing a feasible methodology for rapid nondestructive detection or monitoring of food quality.