Printable FET sensors with using GNH/MnO2 as channel material for non-enzymatic detection of bilirubin.
Saved in:
| Title: | Printable FET sensors with using GNH/MnO2 as channel material for non-enzymatic detection of bilirubin. |
|---|---|
| Authors: | Bui, Duy Hai1 (AUTHOR), Vu, Thi Thu1 (AUTHOR), Piro, Benoit2 (AUTHOR), Nguyen, Thi Thanh Ngan1 (AUTHOR) nguyen-thi-thanh.ngan@usth.edu.vn |
| Source: | Diamond & Related Materials. Apr2025, Vol. 154, pN.PAG-N.PAG. 1p. |
| Subjects: | Graphene oxide, Manganese dioxide, Field-effect transistors, Chemical reduction, Printmaking |
| Abstract: | The accurate detection of bilirubin biomarker is vital for diagnosis of liver diseases. In this study, a novel field-effect-transistor sensor (FET) using aminated reduced graphene oxide flakes (GNH) decorated with manganese dioxide (MnO 2) as channel material has been introduced. The channel material (GNH/MnO 2) was first prepared via in-situ chemical reduction of Mn ions on the aminated reduced graphene oxide flakes, then formulated in ink solution, and finally printed on the channel of the device using extrusion printing method. The results showed the growth of needle-like MnO 2 nanostructure (firmly anchored on graphite flakes) which can act as an excellent catalyst for the oxidation reaction of bilirubin in the later sensing tests. Upon the addition of the targeted molecule (bilirubin), the charge neutrality point was significantly shifted when GNH/MnO 2 was used as the channel material (+25 mV) whereas this point was just slightly shifted (+0.1 mV) when MnO 2 was not introduced. The use of extrusion printing technique has also provided us with a conventional approach to produce low-cost devices with good reproducibility. The as-prepared FET sensors were able to detect bilirubin with a limit of detection (LOD) as low as 10−11 M with good repeatability (relative standard deviation, RSD = 2.64 %). This research has demonstrated the potential application of printable sensing devices integrated with functional nanomaterials as advanced diagnostic tools. [Display omitted] [ABSTRACT FROM AUTHOR] |
| Copyright of Diamond & Related Materials is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
Be the first to leave a comment!
