Abstract

This work demonstrates the development, optimization, and method validation of a square-wave adsorption stripping voltammetry (SWAdSV) method for the simultaneous determination of epinephrine (EP) and uric acid (UA) using a poly(L-cysteine) (pLC) film modified screen-printed carbon electrode (pLC-SPCE). The pLC film was deposited by the electropolymerization of L-cysteine (LC). The successful deposition of pLC was confirmed by time-of-flight secondary ion mass spectrometry. A comparison was made between a bare SPCE and a pLC-SPCE for the analysis of EP and UA. In order to improve the electroanalytical performance of the pLC-SPCE sensor, the parameters of the square-wave (SW) technique, such as amplitude, frequency, and potential step, as well as the pH of the 0.1 M PBS solution, the concentration of the LC, the number of cycles for electropolymerization, the deposition potential, and the deposition time, were optimized. Subsequently, the SWAdSV method was validated for the limit of detection (LOD), the limit of quantification (LOQ), the linear concentration range, accuracy, and precision. The method had a very low LOD and LOQ, i.e. 10.0 µg/L and 19.8 µg/L for both analytes, respectively. Two linear concentration ranges were obtained, i.e. from 49.0 µg/L to 326.1 µg/L and from 326.1 µg/L to 887.1 µg/L, for both analytes. The average recoveries and the relative standard deviations for both analytes were in a range from 94.4% to 108.4% (n = 6) and from 2.6% to 11.7% (n = 6), respectively, at the four EP and UA concentration levels tested. In addition, the effect of possible interferents, such as glucose, L-ascorbic acid, K+, Cl–, Ca2+, SO42–, Mg2+, NH4+, C2O42–, and urea on the SW signal of EP and UA, were investigated. However, none of these compounds significantly affected the performance of the electroanalytical method. Finally, the applicability of the pLC-SPCE sensor was successfully demonstrated for the analysis of a pharmaceutical sample (an EP auto–injector) and human urine, proving accurate and precise analysis using the developed sensor.

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