Reduced graphene oxide decorated with poly(diallyldimethylammonium chloride) for sensitive detection of acetaminophen in water and human urine samples

Ruey Shin Juang*, Chien Te Hsieh*, Ting An Lin, Yu Chia Shao, Yasser Ashraf Gandomi

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

1 Scopus citations

Abstract

In this work, we have developed an efficient electrochemical sensor using screen-printed carbon electrodes (SPCE) modified by reduced graphene oxide-poly(diallyldimethylammonium chloride) (i.e., rGO-PDDA) composites to detect acetaminophen with superior sensitivity and excellent selectivity. The polymerization process resulted in a uniform PDDA coating along with chemically reducing rGO sheets in the presence of hydrazine, thus producing the rGO-PDDA composites. Adopting the Taguchi method with analysis of variances, an optimal parameter set (i.e., rGO/PDDA ratio 1:20, amplitude 100 mV, pulse width 100 ms, and pulse period 0.3 s) with a confidence level of 95% was derived for designing the electrochemical sensors. Accordingly, a linear fit of the signal output versus acetaminophen concentration (r2: 0.9973) was obtained in a wide concentration range (0.794–68.9 μM). The sensitivity of acetaminophen on the SPCE reaches as high as 1.76 μA/(μM cm2) with an ultralow detection limit of 0.0773 μM. The sensitivity of the prepared sensor was also confirmed through exploring the detection of acetaminophen on the SPCE with five interfering species including urea, p-cresol, ascorbic acid, ibuprofen, and 4-aminophenol. The prepared electrode was successfully applied for detecting acetaminophen level in human urine samples. We believed that the robust design of SPCE modified with rGO-PDDA composites demonstrated in this work enables engineering high-performance sensors with superior sensitivity, low detection limit, wide concentration range, and enhanced selectivity toward acetaminophen at ultralow concentrations.

Original languageEnglish
Article number132426
JournalColloids and Surfaces A: Physicochemical and Engineering Aspects
Volume677
DOIs
StatePublished - 20 11 2023

Bibliographical note

Publisher Copyright:
© 2023 Elsevier B.V.

Keywords

  • Acetaminophen
  • Analysis of variance
  • Electrochemical sensor
  • Poly(diallyldimethylammonium chloride)
  • Reduced graphene oxide
  • Taguchi method

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