Optimization of uric acid detection with Au nanorod-decorated graphene oxide (GO/AuNR) using response surface methodology

Hana Safitri; Wulan Tri Wahyuni; Eti Rohaeti; Munawar Khalil; Frank Marken

doi:10.1039/d2ra03782c

Optimization of uric acid detection with Au nanorod-decorated graphene oxide (GO/AuNR) using response surface methodology

RSC Adv. 2022 Sep 7;12(39):25269-25278. doi: 10.1039/d2ra03782c. eCollection 2022 Sep 5.

Authors

Hana Safitri¹, Wulan Tri Wahyuni^{1

2}, Eti Rohaeti¹, Munawar Khalil³, Frank Marken⁴

Affiliations

¹ Analytical Chemistry Division, Department of Chemistry, Faculty of Mathematics and Natural Sciences, IPB University Indonesia wulantriws@apps.ipb.ac.id.
² Tropical Biopharmaca Research Center, Institute of Research and Community Empowerment, IPB University Indonesia.
³ Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Indonesia Depok 16424 Indonesia.
⁴ Department of Chemistry, University of Bath UK.

Abstract

A modified glassy carbon electrode (GCE) was developed based on a synthesized graphene oxide (GO) gold nanorod (AuNR) decorated composite (GO/AuNR) for sensitive electrochemical sensing of uric acid (UA). The electrochemical performance of GO/AuNR/GCE for UA detection was investigated employing the differential pulse voltammetry (DPV) technique. Central composite design (CCD) was applied to obtain the optimum composition of the GO and AuNR composite, which provide the highest possible UA oxidation peak current. The optimum composition was obtained at a GO concentration of 5 mg mL^-1 and AuNR volume of 10 mL. Under the optimum conditions, GO/AuNR/GCE showed acceptable analytical performance for UA detection with good linearity (concentration range of 10-90 μM) and both a low detection limit (0.4 μM) and quantitation limit (1.0 μM). Furthermore, the proposed sensor exhibits superior stability, reproducibility, and selectivity using ascorbic acid (AA), dopamine (DA), urea, glucose, and magnesium as interferents. Finally, practical use of GO/AuNR/GCE was demonstrated by successfully determining the content of UA in human urine samples with the standard addition approach.