Selective non-enzymatic uric acid sensing in the presence of dopamine: electropolymerized poly-pyrrole modified with a reduced graphene oxide/PEDOT:PSS composite

Budi Riza Putra, Ulfiatun Nisa, Rudi Heryanto, Munawar Khalil, Fitri Khoerunnisa, Aga Ridhova, Yudi Nugraha Thaha, Frank Marken, Wulan Tri Wahyuni

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1 Citation (Scopus)

Abstract

A highly selective electrochemical sensor based on a molecularly imprinted polymer (MIP) to be developed for uric acid detection in the presence of dopamine as an interference molecule was demonstrated in this study. This non-enzymatic uric acid sensor was developed by electropolymerizing poly-pyrrole onto a composite of electrochemically reduced graphene oxide (ErGO) and poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) on a glassy carbon electrode (GCE) to give MIP/ErGO/PEDOT:PSS electrodes. The structural properties, surface morphology, and electrochemical interface of this fabricated uric acid sensor was then characterized using infrared spectroscopy, scanning electron microscopy, atomic force microscopy, and electrochemical impedance spectroscopy. This fabricated non-enzymatic electrochemical sensor (MIP/ErGO/PEDOT:PSS modified GCE) also showed excellent analytical performance at the optimum ratio of monomer/template concentration and optimized electropolymerization conditions, for example in the low concentration range of 0.1-100 μM with a detection limit of 0.05 μM towards uric acid detection in the presence of dopamine. Furthermore, this fabricated uric acid sensor also exhibited good reproducibility and stability for uric acid measurements in the presence of dopamine for 5 consecutive days. In addition, this sensor demonstrates highly selective detection of uric acid in the presence of several interfering species such as dopamine, urea, glucose, magnesium ions, and ascorbic acid. This fabricated uric acid sensor ultimately showed satisfactory uric acid measurement in samples of human urine and is expected to be used in early-stage disease diagnosis.

Original languageEnglish
Pages (from-to)5334-5346
Number of pages13
JournalAnalyst
Volume147
Issue number23
DOIs
Publication statusAccepted/In press - 2022

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