Experimental characterization, machine learning analysis and computational modelling of the high effective inhibition of copper corrosion by 5‐(4‐pyridyl)‐1, 3, 4‐oxadiazole‐2‐thiol in saline environment. (1st December 2021) - Varvara, Simona; Berghian-Grosan, Camelia; Bostan, Roxana; Ciceo, Raluca Lucacel; Salarvand, Zohreh; Talebian, Milad; Raeissi, Keyvan; Izquierdo, Javier; Souto, Ricardo M.
Highlights: Copper protection in 3.5 wt.%NaCl by 5-(4-pyridyl)-1, 3, 4-oxadiazole-2-thiol (PyODT). High inhibitive efficacy of PyODT on Cu corrosion was reached at long exposure. A uniform and compact inhibitor film was formed on copper surface. Interaction between Cu and PyODT proceeded through thiol and oxadiazole groups. Machine learning algorithms and Raman data were firstly applied in corrosion study. Abstract: An oxadiazole derivative with functional groups favouring its adsorption on copper surface, namely 5-(4-pyridyl)-1, 3, 4-oxadiazole-2-thiol, has been explored as potential inhibitor of copper corrosion in 3.5 wt.% NaCl. Electrochemical evaluation by electrochemical impedance spectroscopy, potentiodynamic polarization and SVET reveals high inhibition efficiencies. Surface microscopy inspection and spectroscopic analysis by Raman, SEM-EDX and XPS highlight the formation of a compact barrier film responsible for long-lasting protection, that is mainly composed of the organic molecules. Machine learning algorithms used in combination with Raman spectroscopy data were applied successfully for the first time in corrosion studies to allow discrimination between corroded and inhibitor-protected metal surfaces. Quantum Chemistry calculations in aqueous solution and Molecular Dynamic studies predict a strong interaction between copper and the thiol group and an extensive coverage of the metal surface, responsible for the excellent protection against corrosion. Graphical abstract: Image, graphical abstract .