AI-powered graphene tongue detects flavors with 98% precision

Scientists have developed an AI-powered artificial tongue using graphene oxide within a nanofluidic device that mimics human taste with remarkable accuracy. This system integrates both sensing and computing on a single platform, enabling it to detect chemical signals and classify flavors in real time, even in moist conditions similar to the human mouth. Trained on 160 chemicals representing common flavors, the device achieved about 98.5% accuracy in identifying known tastes (sweet, salty, sour, and bitter) and 75-90% accuracy on 40 new flavors, including complex mixtures like coffee and cola. This breakthrough marks a significant advancement over previous artificial taste systems by combining sensing and processing capabilities. The sensor exploits graphene oxide’s sensitivity to chemical changes, detecting subtle conductivity variations when exposed to flavor compounds. Coupled with machine learning, it effectively recognizes flavor patterns much like the human brain processes taste signals. The researchers highlight potential applications such as restoring taste perception for individuals affected by stroke or viral infections, as well as uses