![]() ![]() ![]() Thanks to its mechanical flexibility 8, graphene can potentially enable innately flexible form-factors in contrast to silicon-based sensing systems. In contrast to traditional metal oxide-based chemo-resistor sensors, which suffer from high humidity sensitivity, graphene is stable and chemically inert 7. The high carrier mobility 6, which translates into high transconductance, makes graphene a more desirable transducer compared to organic materials such as poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS). It has the largest surface-to-volume ratio 5 and exhibits a number of promising characteristics. Graphene is the most widely studied material among all 2D materials and provides the most mature material synthesis 4. Two-dimensional (2D) materials are particularly promising in biochemical sensing applications thanks to their large-surface-to-volume ratio, which allows the sensor channel to be readily modulated upon chemical changes near the surface, translating chemical signals into the electrical or optical domain with enhanced sensitivity. Such systems are commonly multiplexed to identify different analytes or provide active calibration 1. Smart sensors, such as sweat sensors, targeting various physiologically-relevant biomarkers in biofluids have recently demonstrated great potential for health-tracking and medical diagnosis 1, 2, 3. A calibration method leveraging the sensor redundancy and device-to-device variation is also proposed, while a machine learning model trained with multi-dimensional information collected through the multiplexed sensor array is used to enhance the sensing system’s functionality and accuracy in ion classification. The platform demonstrates reconfigurable multi-ion electrolyte sensing capability and provides highly sensitive, reversible, and real-time response for potassium, sodium, and calcium ions in complex solutions despite variations in device performance. Here, we develop a robust bioelectronic sensing platform composed of more than 200 integrated sensing units, custom-built high-speed readout electronics, and machine learning inference that overcomes these challenges to achieve rapid, portable, and reliable measurements. Two-dimensional materials such as graphene have shown great promise as biosensors, but suffer from large device-to-device variation due to non-uniform material synthesis and device fabrication technologies. ![]()
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