Three-Dimensional Voltammetry: A Chemometrical Analysis of Electrochemical Data for Determination of Dopamine in the Presence of Unexpected Interference by a Biosensor Based on Gold Nanoparticles

Multivariate curve resolution by alternating least-squares (MCR-ALS) was used for voltammetric determination of dopamine (DA) in the presence of epinephrine (EP) at a gold nanoparticles chemically modified carbon paste electrode (AuNPs/CPE). Scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), and cyclic voltammetry (CV) techniques were applied for characterization of the nanostructure modified electrode. Central composite rotatable design (CCRD) was employed to generate an experimental program to offer data to model the effects of different parameters on voltammetric responses. Response surface methodology (RSM) was applied to show the individual and interactive effects of chemical and instrumental variables at five levels, combined according to CCRD. For determination of DA in the presence of unexpected interference, three-way data were achieved from various pulse heights in differential pulse voltammetry (DPV) technique. This type of data construction, analyzed by MCR-ALS, makes it possible to exploit the so-called “second-order advantage”. The second-order advantage provided unbiased results even in the presence of electroactive interferences with highly overlapped peaks. Also, an algorithm was applied to correct the detected potential shift in the voltammetric data. The voltammograms of the samples were then deposited in an augmented data matrix (column-wise) and subsequently analyzed by MCR-ALS. The effect of rotational ambiguity associated with a particular MCR-ALS solution under a set of constraints was also studied. The proposed method could be applied for the determination of DA and EP in the presence of each other in a wide concentration range of 0.1–205.0 μM, and the detection limit of DA has been found to be 35.5 nM. Finally, the technique has been used for the reliable analysis of DA in real samples