Details

Autor(en) / Beteiligte

• Hwang, Hye Suk
• Jeong, Jae Won
• Kim, Yoong Ahm
• Chang, Mincheol

Titel

Carbon Nanomaterials as Versatile Platforms for Biosensing Applications

Ist Teil von

• Micromachines (Basel), 2020-08, Vol.11 (9), p.814

Ort / Verlag

Basel: MDPI AG

Erscheinungsjahr

2020

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• A biosensor is defined as a measuring system that includes a biological receptor unit with distinctive specificities toward target analytes. Such analytes include a wide range of biological origins such as DNAs of bacteria or viruses, or proteins generated from an immune system of infected or contaminated living organisms. They further include simple molecules such as glucose, ions, and vitamins. One of the major challenges in biosensor development is achieving efficient signal capture of biological recognition-transduction events. Carbon nanomaterials (CNs) are promising candidates to improve the sensitivity of biosensors while attaining low detection limits owing to their capability of immobilizing large quantities of bioreceptor units at a reduced volume, and they can also act as a transduction element. In addition, CNs can be adapted to functionalization and conjugation with organic compounds or metallic nanoparticles; the creation of surface functional groups offers new properties (e.g., physical, chemical, mechanical, electrical, and optical properties) to the nanomaterials. Because of these intriguing features, CNs have been extensively employed in biosensor applications. In particular, carbon nanotubes (CNTs), nanodiamonds, graphene, and fullerenes serve as scaffolds for the immobilization of biomolecules at their surface and are also used as transducers for the conversion of signals associated with the recognition of biological analytes. Herein, we provide a comprehensive review on the synthesis of CNs and their potential application to biosensors. In addition, we discuss the efforts to improve the mechanical and electrical properties of biosensors by combining different CNs.