Development of a novel electrochemical sensor based on electropolymerized molecularly imprinted polymer for selective detection of sodium lauryl sulfate in environmental waters and cosmetic products

In this study, a novel molecularly imprinted polymer (MIP) sensor for the electrochemical detection of sodium lauryl sulfate (SLS) is reported. The MIP based screen-printed gold electrode (Au-SPE) was prepared by an electrochemical polymerization of 2-aminothiophenol (2-ATP) in the presence of SLS as target molecule. For control, a non-imprinted polymer (NIP) sensor was also constructed identically by omitting the SLS template. Moreover, the selectivity of the proposed MIP sensor was investigated by using analogues such as Ethylenediaminetetraacetic acid (EDTA), Tween 80 and Urea, revealing satisfactory selectivity toward SLS. The electrochemical characterization of the elaborated sensor was performed using cyclic voltammetry (CV), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS) techniques. The morphology of the MIP sensor was studied by means of Atomic Force Microscopy (AFM) and Fourier Transform Infrared Spectroscopy (FTIR) methods. Some experimental parameters such as number of cycle for the electropolymerization, incubation time of 2-ATP, elution and SLS incubation time, were optimized to improve the sensor performances. Under optimal conditions, the electrochemical sensor exhibits a logarithmic working range from 0.1 to 1000 pg/mL, and a detection limit of 0.18 pg/mL. Additionally, compared with reported works, the sensor possesses remarkable properties, such as a higher sensitivity and selectivity, a good reproducibility, a wider logarithmic range, a lower detection limit and a long-term stability. As real application, the developed MIP sensor was well employed to determine SLS contents in environmental waters and cosmetic products samples. A UV-vis spectrophotometer was used as reference method. A partial least squares (PLS) technique was well employed to study the correlation between the spectrophotometer and the MR) sensor technology with a satisfactory regression coefficient (R = 0.99). The obtained results during the sensor development and applications suggested an interesting and valuable tool for environmental analysis.