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​Researchers design a graphene-based ‘electronic tongue’ that detects liquid differences, spoilage, and food safety with AI accuracy 

​Researchers design a graphene-based ‘electronic tongue’ that detects liquid differences, spoilage, and food safety with AI accuracy 

Researchers from Penn State University and NASA Goddard Space Flight Center recently developed an ‘electronic tongue’ based on a graphene-based ion-sensitive field-effect transistor, capable of identifying differences in similar liquids, such as milk with varying water content; diverse products, including soda types and coffee blends; signs of spoilage in fruit juices; and instances of food safety concerns. The team also found that results were even more accurate when artificial intelligence (AI) used its own assessment parameters to interpret the data generated by the electronic tongue.

Graphene ISFET chip mounted on a printed circuit board (PCB). Image from: Nature

The sensor and AI can broadly detect and classify various substances while collectively assessing their respective quality, authenticity and freshness. This assessment has also provided the researchers with a view into how AI makes decisions, which could lead to better AI development and applications, they said.

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Researchers from Penn State University and NASA Goddard Space Flight Center recently developed an ‘electronic tongue’ based on a graphene-based ion-sensitive field-effect transistor, capable of identifying differences in similar liquids, such as milk with varying water content; diverse products, including soda types and coffee blends; signs of spoilage in fruit juices; and instances of food safety concerns. The team also found that results were even more accurate when artificial intelligence (AI) used its own assessment parameters to interpret the data generated by the electronic tongue.

Graphene ISFET chip mounted on a printed circuit board (PCB). Image from: Nature
The sensor and AI can broadly detect and classify various substances while collectively assessing their respective quality, authenticity and freshness. This assessment has also provided the researchers with a view into how AI makes decisions, which could lead to better AI development and applications, they said. 

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