Utility of (MgO)12 nanocage as a chemical sensor for recognition of amphetamine drug: A computational inspection

Abstract

DFT calculations on sensor-drug interactions are necessary for understanding binding mechanisms, predicting sensor performance, evaluating stability and reactivity, and rational design of sensor materials. We scrutinized the adsorption of amphetamine (AFE) on the pure magnesium oxide nano-cage (MgONC) by applying density functional theory. All geometries and single point energy computations were optimized at M06–2X/6–311 G (d, p). Furthermore, we performed an analysis of the natural bond orbital (NBO) and evaluated the values of partial natural charges. Additionally, we investigated donor-acceptor (D-A) interactions and examined the Wiberg bond index (WBI) in greater depth. The MgONC was capable of adsorbing AFE with greater strength with the energy of adsorption (Eads) of −48.19 kcal/mol (for stable configurations). Moreover, the NBO method demonstrated more effective D-A interactions between AFE and the MgONC. Based on the computations, for the most stable configuration, there was a substantial alteration in the HOMO-LUMO gap of the MgONC following the drug adsorption, thus increasing the electrical conductance (EC) of the MgONC. The sensing mechanism is related to the gap difference, which depends on the change in the EC. We adopted the conventional transition state theory for the prediction of recovery time. The computations indicated that the MgONC+ AFE configuration had a short recovery time for the desorption of AFE. Finally, based on our findings, we could conclude that the MgONC is an appropriate choice for the improvement of effective AFE sensors. DFT study of drug sensors will focus on enhancing sensitivity, selectivity, and stability while exploring novel materials and optimizing performance through theoretical simulations and analysis.

Keywords

• Amphetamine
• Sensors
• Recovery time
• Adsorption energy
• Electrical conductance