晶体管
纳米技术
范围(计算机科学)
场效应晶体管
生物分子
生物传感器
灵敏度(控制系统)
材料科学
计算机科学
电子工程
工程类
电气工程
电压
程序设计语言
作者
N. K. Murugasenapathi,Rituparna Ghosh,Santheraleka Ramanathan,Soumalya Ghosh,Amutha Chinnappan,S. Jamal Mohamed,K. A. Esther Jebakumari,Subash C. B. Gopinath,Seeram Ramakrishna,Tamilarasan Palanisamy
标识
DOI:10.1080/10408347.2021.2002133
摘要
AbstractAbstractTransistor-based sensors have been widely recognized to be highly sensitive and reliable for point-of-care/bed-side diagnosis. In this line, a range of cutting-edge technologies has been generated to elevate the role of transistors for biomolecule detection. Detection of a wide range of clinical biomarkers has been reported using various configurations of transistors. The inordinate sensitivity of transistors to the field-effect imparts high sensitivity toward wide range of biomolecules. This overview has gleaned the present achievements with the technological advancements using high performance transistor-based sensors. This review encloses transistors incorporated with a variety of functional nanomaterials and organic elements for their excellence in selectivity and sensitivity. In addition, the technological advancements in fabrication of these microdevices or nanodevices and functionalization of the sensing elements have also been discussed. The technological gap in the realization of sensors in transistor platforms and the resulted scope for research has been discussed. Finally, foreseen technological advancements and future research perspectives are described.Keywords: Biomoleculefield-effectminiaturizationnanostructuresorganicsensortransistor Additional informationFundingThe authors (P. T, J. M and N. K. M) would like to acknowledge the financial support, Grant No. SRG/2019/001044, provided by Science & Engineering Research Board (SERB), India. Prof. Seeram acknowledges the support by both Lloyd's Register Foundation, UK (Grant No: R265000553597), NUS Hybrid-Integrated Flexible (Stretchable) Electronic Systems (HiFES) Program Seed Fund (Grant No. R265000628133) and iGrants Project no A1783c0012 (Grant No.R265000606305).
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