Our study aims to implement a strategy to reduce the carbon steel corrosion rate in a sulfuric acid solution, using an expired drug with adsorption affinity on the metal surface. To investigate the corrosion protection efficiency of an environmental friendly inhibitor, namely neomycin sulfate (NMS), the electrochemical measurements were applied on carbon steel immersed in 1.0 M H₂SO₄ solution with and without NMS. The protective layer that formed on the steel surface was studied by atomic force microscopy (AFM). The potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) showed that the presence of the neomycin sulfate in acid solution leads to the decrease in corrosion current density (i_corr) and the increase of polarization resistance (R_p). The mixed mechanism between physical and chemical adsorption of NMS molecules on the steel surface was proposed according to the Langmuir adsorption isotherm. AFM indicated that the NMS molecules contributed to a protective layer formation by their adsorption on the steel surface. The AFM parameters, such as root mean square roughness (R_q), average roughness (R_a), and maximum peak to valley height (R_p−v) revealed that in the presence of NMS a smoother surface of carbon steel was obtained, compared to the steel surface corroded in sulfuric acid blank solution.

In order to assemble effective protective coatings against corrosion, electrochemical techniques such as linear potentiometry and cyclic voltammetry were performed on a copper surface in 0.1 mol·L⁻¹ HCl solution containing 0.1% polyvinyl alcohol (PVA) in the absence and presence of silver nanoparticles (nAg/PVA). A recent paradigm was used to distinguish the features of the coatings, that is, a deep convolutional neural network (CNN) was implemented to automatically and hierarchically extract the discriminative characteristics from the information given by optical microscopy images. In our study, the material surface morphology, controlled by the CNN without the interference of the human factor, was successfully conducted to extract the similarities/differences between unprotected and protected surfaces in order to establish the PVA and nAg/PVA performance to retard copper corrosion. The CNN results were confirmed by the classical investigation of copper behavior in hydrochloric acid solution in the absence and presence of polyvinyl alcohol and silver nanoparticles. The electrochemical measurements showed that the corrosion current density (i_corr) decreased and polarization resistance (R_p) increased, with both PVA and nAg/PVA being effective inhibitors for copper corrosion in an acid environment, forming polymer protective coatings by adsorption on the metal surface. Furthermore, scanning electron microscopy (SEM) certifies the formation of polymer coatings, revealing a specific morphology of the copper surface in the presence of PVA and nAg/PVA, very different from that of corroded copper in uninhibited solutions. Finally, the correlation of the CNN information with experimental data was reported.

Inhibitive properties of the antibacterial sulfa drug sulfathiazole—IUPAC name being 4-amino-N-(1,3-thiazol-2-yl) benzene sulfonamide—on the corrosion of carbon steel in 1.0 M HCl solution were investigated using weight loss measurements, electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). Sulfathiazole is a good adsorption inhibitor, and the inhibition efficiency increases with increasing concentration. Adsorption is spontaneous and is best described by Temkin isotherm. XPS analysis showed, at this stage, that the main product of corrosion is a nonstoichiometric Fe³⁺ oxide/oxyhydroxide consisting of a mixture of Fe₂O₃, α, and γ-FeO(OH) and/or Fe(OH)₃, where α, γ-FeO(OH) is the main phase.