摘要
Paracetamol, a popular analgesic, has been linked to harmful health effects, such as kidney and liver damage. The detection of paracetamol in the environment and its overdose use in humans and animals has raised global concerns, highlighting the need for its efficient removal or detection in real samples. In this study, a deep eutectic solvent-molecularly imprinted polymer (DES-MIP) was synthesized and applied as an adsorbent to recognize the removal of paracetamol selectively. DES-MIP was synthesized using a deep eutectic solvent (DES) as a functional monomer, ethylene glycol dimethacrylate as a crosslinker, and paracetamol as a template. DES was initially prepared by combining choline chloride (ChCl) with methacrylic acid at a molar ratio of 1:2. A deep eutectic solvent-non-imprinted polymer (DES-NIP) was synthesized as a control. The characterization analysis, including Fourier transform infrared spectroscopy (FTIR), Scanning emission microscopy (SEM), and Brunauer-Emmett-Teller (BET) was conducted for both polymers to confirm the synthesis occurred. The selectivity study inferred that DES-MIP (15.95 mg/g) was more selective towards paracetamol than DES-NIP (7.00 mg/g). Response surface methodology (RSM) coupled with central composite design (CCD) was employed to examine the effect of pH, contact time, and dosage on paracetamol adsorption. The analysis of variance (ANOVA) demonstrated the relative significance of process parameters in the adsorption process. The contact time and dosage were found to be more significant than the pH. The result indicated that the optimal conditions for paracetamol adsorption were pH 7, 35 min, and 5.5 mg. The behavior of paracetamol adsorption on DES-MIP was well-fitted using the second-order kinetic and Langmuir isothermal models, respectively. Then, the DES-MIP with optimized parameter studies was applied to herbs, medicine, and dietary supplements, achieving good recoveries of 94.46 %, 86.79 %, and 85.13 % and relative standard deviations (RSD) of 1.15 %, 2.39 %, and 2.52 %, respectively.