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Computational Foretelling and Experimental Implementation of the Performance of Polyacrylic Acid and Polyacrylamide Polymers as Eco-Friendly Corrosion Inhibitors for Copper in Nitric Acid

Research Authors
Arafat Toghan, Ahmed Fawzy, Areej Al Bahir, Nada Alqarni, Moustafa M. S. Sanad , Mohamed Khairy, Abbas I. Alakhras, Ahmed A. Farag
Research Abstract

Copper is primarily used in many industrial processes, but like many other metals, it suffers from corrosion damage. Polymers are not only one of the effective corrosion inhibitors but also are environmentally friendly agents in doing so. Hence, in this paper, the efficacy of two polyelectrolyte polymers, namely poly(acrylic acid) (PAA) and polyacrylamide (PAM), as corrosion inhibitors for copper in molar nitric acid medium was explored. Chemical, electrochemical, and microscopic tools were employed in this investigation. The weight-loss study revealed that the computed inhibition efficiencies (% IEs) of both PAA and PAM increased with their concentrations but diminished with increasing HNO3 concentration and temperature. The results revealed that, at similar concentrations, the values of % IEs of PAM are slightly higher than those recorded for PAA, where these values at 298 K reached 88% and 84% in the presence of a 250 mg/L of PAM and PAA, respectively. The prominent IE% values for the tested polymers are due to their strong adsorption on the Cu surface and follow the Langmuir adsorption isoform. Thermodynamic and kinetic parameters were also calculated and discussed. The kinetics of corrosion inhibition by PAA and PAM showed a negative first-order process. The results showed also that the used polymers played as mixed-kind inhibitors with anodic priority. The mechanisms of copper corrosion in nitric acid medium and its inhibition by the tested polymers were discussed. DFT calculations and molecular dynamic (MD) modelling were used to investigate the effect of PAA and PAM molecular configuration on their anti-corrosion behavior. The results indicated that the experimental and computational study are highly consistent.

Research Date
Research Journal
Polymers
Research Member
Research Publisher
MDPI
Research Rank
1
Research Vol
14
Research Year
2022
Research Pages
1-23