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Integrated biosensor platform based on graphene transistor arrays for real-time high-accuracy ion sensing

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. Here, we develop a robust bioelectronic sensing platform  composed of  more than 200 integrat...

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Detalles Bibliográficos
Autores principales: Xue, Mantian, Mackin, Charles, Weng, Wei-Hung, Zhu, Jiadi, Luo, Yiyue, Luo, Shao-Xiong Lennon, Lu, Ang-Yu, Hempel, Marek, McVay, Elaine, Kong, Jing, Palacios, Tomás
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420106/
https://www.ncbi.nlm.nih.gov/pubmed/36030295
http://dx.doi.org/10.1038/s41467-022-32749-4
Descripción
Sumario: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. 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. 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. 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.