BBD Design for optimization of the fabrication a selective nano-electrochemical flexible carbon cloth sensor assembled by AuCDs imprinted by polydopamine to Orlistat accurate repeatable detection

One of the cutting-edge emerging approaches being used by researchers in the field of sensors is to go beyond conventional techniques and design flexible, portable, selective sensors that can swiftly and accurately identify trace quantities of target molecules. In this research carbon cloth, as a binder-free 3D flexible material, served as the working electrode. In a single step, hydrothermal approach AuCD nanoparticles were synthetized and used to modify the carbon cloth surface. The molecular imprinting polymer approach using in situ electropolymerization of dopamine monomer in the presence of orlistat as the target molecule utilized to fabricate imprinted sensor [1, 2]. To achieve the most promising results, experimental design used to optimize the variables and instrumental parameters. In comparison to a one-at-a-time experiment, this method requires fewer measurements and can estimate how the elements interact [3]. The statistical significance of a list of the main and interaction effects is assessed using an analysis of variance (ANOVA) table. Utilizing Minitab (Version 21) software, the synergistic effects of the five variables (Electropolymerization pH (A), DA to OST ratio (B), number of CV scan cycles (C), KOH concentration (D), OST elution time (E)) on the DPV response were optimized. One of the most useful optimization techniques, the response surface approach (Box-Behnken model), was utilized to improve crucial experimental factors impacting MIP preparation. In the conditions of pH = 8, dopamine to orlistat ratio = 2.5, electroploymerization cycle number = 30, KOH = 3.5 M, elution time = 20.4 min, and 0.0005 to 1.3 nM linear range with a detection limit of 0.0002 nM, the best response was obtained for the accurate identification of the orlistat by the architected sensor. SEM and ATR-FTIR analysis were used to characterize and survey the correctness of the sensor manufacturing. The stability, selectivity, and performance of the presented sensor were evaluated under optimal conditions. Using blood serum and urine samples, satisfactory outcomes were achieved in real samples. This is the first electrochemical sensor report for orlistat detection to date.