Issue 33, 2017

A label-free and universal platform for the construction of an odd/even detector for decimal numbers based on graphene oxide and DNA-stabilized silver nanoclusters

Abstract

Molecular logic devices with different functions can perform various tasks in the areas of biological molecule detection, disease diagnosis, multivariate analysis, and bioimaging. Herein, a series of logic circuits based on silver nanoclusters (AgNCs)/graphene oxide (GO) are constructed to execute nonarithmetic functions, including 3-, 4-, and 5-bit odd/even checking. The resulting devices can differentiate between even and odd decimal numbers in the range from 0 to 31. Moreover, the devices can be expanded to operate with wider ranges of numbers when more inputs are added. The signal reporter is structured using AgNCs and GO, preventing laborious modification of biomolecules. The designed DNA-based logic nanodevices share the same DNA platform and a constant threshold value, showing great potential for application in information processing at the molecular level. Additionally, these devices can stably carry out their logic operations in a biological matrix, indicating that the AgNC/GO-based system can operate in a complicated biological environment. Given the biocompatibility and design flexibility of DNA, this study provides novel outcomes towards the development of label-free intelligent nanodevices. This may open a new path for the application of AgNCs/GO in molecular logic circuits and fluorescence imaging.

Graphical abstract: A label-free and universal platform for the construction of an odd/even detector for decimal numbers based on graphene oxide and DNA-stabilized silver nanoclusters

Supplementary files

Article information

Article type
Paper
Submitted
23 May 2017
Accepted
20 Jul 2017
First published
21 Jul 2017

Nanoscale, 2017,9, 11912-11919

A label-free and universal platform for the construction of an odd/even detector for decimal numbers based on graphene oxide and DNA-stabilized silver nanoclusters

S. Zhang, K. Wang, K. Li, F. Chen, W. Shi, W. Jia, J. Zhang and D. Han, Nanoscale, 2017, 9, 11912 DOI: 10.1039/C7NR03670A

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