2021
DOI: 10.1002/elsa.202100137
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Recent advances in field‐effect transistor sensing strategies for fast and highly efficient analysis of heavy metal ions

Abstract: Heavy metal ions are highly toxic for living organisms especially after bioaccumulation and biomagnification, which possess a serious threat to human health and ecological environment. The rapid, portable, and efficient analytical methods are urgently needed for the determination of heavy metals in different media. Due to the unique advantages of field‐effect transistor (FET) sensors including fast response, easy manipulation, small size, and high sensitivity, FET sensor has become a novel strategy for heavy m… Show more

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Cited by 14 publications
(9 citation statements)
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“…113 Conventional spectroscopic methods such as atomic adsorption spectroscopy, atomic absorption spectroscopy, and inductively coupled plasma mass spectrometry (ICP-MS) have been mostly employed to detect heavy metals; however, they require a complex instrumental setup (e.g., rooms for instrument or trained operators) and are time-consuming owing to complicated procedures such as pretreatment and measurement, making them inappropriate for on-site monitoring. 114 A label-free biosensor for Cu (II), based on a graphene FET functionalized with structure-switching aptamer probes against Cu (II), is applicable. To compare Cu(II) concentrations in real fish samples using results obtained from ICP-MS, a traditional method used to analyze heavy metals, demonstrated through the FET sensor system in this study and exhibited good accuracy for the determination of Cu 2+ ions in samples.…”
Section: Ecosystem Monitoring With Electrical Sensormentioning
confidence: 99%
“…113 Conventional spectroscopic methods such as atomic adsorption spectroscopy, atomic absorption spectroscopy, and inductively coupled plasma mass spectrometry (ICP-MS) have been mostly employed to detect heavy metals; however, they require a complex instrumental setup (e.g., rooms for instrument or trained operators) and are time-consuming owing to complicated procedures such as pretreatment and measurement, making them inappropriate for on-site monitoring. 114 A label-free biosensor for Cu (II), based on a graphene FET functionalized with structure-switching aptamer probes against Cu (II), is applicable. To compare Cu(II) concentrations in real fish samples using results obtained from ICP-MS, a traditional method used to analyze heavy metals, demonstrated through the FET sensor system in this study and exhibited good accuracy for the determination of Cu 2+ ions in samples.…”
Section: Ecosystem Monitoring With Electrical Sensormentioning
confidence: 99%
“…While the stability can be improved by protection of the sensor structure through passivation or packaging, the development of low-cost sensors that can measure water contaminants accurately in the field setting will represent a major development in water sensing. [7,71] Technically, low-cost monitoring of water contaminants is promising when accompanied by scaled-up fabrication of FET/TFET sensor devices, but there are some hurdles regarding performance metrics that need to be overcome in real-world settings. The simultaneous detection of multiple types of contaminants with a high accuracy is the foremost performance metric that requires both classification of contaminant species and their quantification.…”
Section: Case Study Ii: Potential Water Sensor Testbeds For Intelligent Water Systemsmentioning
confidence: 99%
“…Conventional methods can determine metal atoms; however, identifying the type of metal compound is difficult, which poses a significant limitation in determining the leakage of heavy metals in water. In addition, sensors focusing on heavy-metal compounds have not been realized in the heavy-metal sensors that were reported in recent years [ 6 , 14 ]. Therefore, this study aims to develop a compact sensor using graphene and chelating agents that is capable of the early detection of cadmium and the identification of cadmium compounds in water.…”
Section: Introductionmentioning
confidence: 99%