Silver nanoparticle on zinc oxide array for label-free detection of opioids through surface-enhanced raman spectroscopy

Document Type

Article

Publication Date

3-3-2021

Abstract

Opioid abuse is a significant public health problem. Over two million Americans have some form of addiction to opioids; however, despite governmental programs established to treat overdoses and restrict opioid distribution, there are still few screening tools that are quantitative, portable and easy to use for high-throughput mapping and monitoring this ongoing crisis. In this paper, we demonstrated a plasmonic zinc oxide (ZnO) arrays-on-silicon sensor for the label-free detection of opioids through surface-enhanced Raman spectroscopy (SERS), and evaluated the chips' opioid sensing performance. Specifically, we tested our device with oxycodone, a potent and commonly abused opioid, dissolved in methanol and blood serum as a proof-of-concept study. Ag particles werein situpatterned onto the ZnO array to form the completed sensing platform. The resulting Ag@ZnO arrays were characterized using Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Analysis (EDS), and element mapping. In addition, the enhanced electric field induced by the localized surface plasmonic resonance at the Ag particle decorated ZnO is simulated using COMSOL. Opioid-containing samples at varying concentrations, from 900 μg mL−1to 90 ng mL−1were tested using SERS to characterize the chip's accuracy and sensitivity. We demonstrated that the sensor can reliably detect opioid concentrations as low as 90 ng mL−1with great accuracy and sensitivity even spiked into blood serum. The chips could provide a cost-effective, high-throughput method for detecting opiate oxycodone, thereby providing a powerful tool to monitor and control the emerging public health threats.

Identifier

85103167093 (Scopus)

Publication Title

Rsc Advances

External Full Text Location

https://doi.org/10.1039/d1ra00760b

e-ISSN

20462069

First Page

11329

Last Page

11337

Issue

19

Volume

11

Grant

ECCS1509369

Fund Ref

National Science Foundation

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