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Location
3rd Floor Café Commons of the Millennium Science Complex
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Ion-sensitive field-effect transistors (ISFETs) have become useful for chemosensing (translating chemical composition changes into electrical signals) with applications in environmental monitoring, healthcare diagnostics, and industrial control. This work explores the integration of machine learning with graphene-based ISFETs, using extensive sensor data for classification and quantification tasks. Specifically, data from non-functionalized graphene-based ISFETs are used to train neural networks to detect issues like food fraud and spoilage, showing potential for data-driven chemical detection across diverse applications.