石墨烯
生物传感器
计算机科学
冗余(工程)
ISFET
数码产品
多路复用
材料科学
制作
纳米技术
晶体管
场效应晶体管
电压
电气工程
电信
工程类
医学
替代医学
病理
操作系统
作者
Mantian Xue,Charles Mackin,Wei‐Hung Weng,Jiadi Zhu,Yiyue Luo,Shao‐Xiong Lennon Luo,Ang‐Yu Lu,Marek Hempel,Elaine McVay,Jing Kong,Tomás Palacios
标识
DOI:10.1038/s41467-022-32749-4
摘要
Abstract 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.
科研通智能强力驱动
Strongly Powered by AbleSci AI