TY - JOUR
T1 - Reduced graphene oxide decorated with poly(diallyldimethylammonium chloride) for sensitive detection of acetaminophen in water and human urine samples
AU - Juang, Ruey Shin
AU - Hsieh, Chien Te
AU - Lin, Ting An
AU - Shao, Yu Chia
AU - Gandomi, Yasser Ashraf
N1 - Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2023/11/20
Y1 - 2023/11/20
N2 - 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.
AB - 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.
KW - Acetaminophen
KW - Analysis of variance
KW - Electrochemical sensor
KW - Poly(diallyldimethylammonium chloride)
KW - Reduced graphene oxide
KW - Taguchi method
UR - http://www.scopus.com/inward/record.url?scp=85171435919&partnerID=8YFLogxK
U2 - 10.1016/j.colsurfa.2023.132426
DO - 10.1016/j.colsurfa.2023.132426
M3 - 文章
AN - SCOPUS:85171435919
SN - 0927-7757
VL - 677
JO - Colloids and Surfaces A: Physicochemical and Engineering Aspects
JF - Colloids and Surfaces A: Physicochemical and Engineering Aspects
M1 - 132426
ER -