Nonenzymatic Electrochemical Sensor Based on CuO-MgO Composite for Dopamine Detection

Dopamine plays an essential role in the proper functioning of the brain and the body. A change in the level of dopamine can lead to disorders related to the nervous system. Thus, detection of dopamine levels may aid in the diagnosis and treatment of various diseases. Enzymatic electrochemical sensors have been extensively studied for the detection of dopamine because they exhibit excellent selectivity and reliability. However, enzymatic electrochemical sensors suffer from several unavoidable drawbacks such as complex enzyme purification process, weak enzyme immobilization on the electrode, enzyme denaturation and low stability. On the other hand, non-enzymatic sensors are promising alternatives that offer high sensitivity, high electrocatalytic activity, long term stability and eliminate the problems associated with enzymes. Herein, we present a non-enzymatic nanocomposite (NC) of metal oxides (CuO-MgO) for efficient electrochemical detection of dopamine. Scalable sol-gel method is adopted for the controlled growth of CuO-MgO NC. The structural, elemental and morphological analysis is performed by XRD, Raman spectroscopy, and TEM characterization, respectively. The electrochemical analysis was carried out to study the electrocatalytic behavior of CuO-MgO in the detection of dopamine, by cyclic voltammetry and chronoamperometric methods. The electrocatalytic behavior was investigated at different scan rates and for different dopamine concentrations in artificial sweat solution. The CuO-MgO NC catalyst exhibited a sensitivity of $69~\mu $ Acm−2mM−1 and the detection limit is computed to be $6.4~\mu \text{M}$ in the linear range of 10- $100~\mu \text{M}$ . Moreover, the NC apprehended a high degree of selectivity towards other bio-compounds present in the sweat, and no possible interfering cross-reaction from these species was observed. The as-synthesized CuO-MgO NC offered high sensitivity, selectivity, fast response and stability, which benchmarked its potential for dopamine sensing.