Qatar Foundation Annual Research Conference Proceedings Volume 2018 Issue 1

Microbial Influenced Corrosion (MIC) is a process influenced by various microorganisms especially by sulfate reducing bacteria (SRB) which affects the kinetics of corrosion procedure under anaerobic conditions. About 20% of the annual corrosion damages of metals may be produced by microbial activities especially due to anaerobic corrosion influenced by SRB. MIC is the main contributor of corrosion problems and a leading cause of pipeline failure in oil and gas industries. SRBs are main microorganisms that can anaerobically generate sulfide species causing biocorrosion in the injection networks. Moreover, the produced H2S gas is toxic, corrosive, and responsible for a variety of environmental problems. Additionally, the presence of SRB can result in health and safety risks to workers due to sulfide production. In order to prevent this, oil-producing companies use high concentrations of biocides to disinfect the water and inhibit excessive biofilm formation caused mainly by (SRB). However, traditional biocides may be harmful to environment by forming harmful disinfection byproducts. Also the biocide treatment having other disadvantages like low efficiency against biofilms, release of disinfection byproducts and its high cost. Theses disadvantages can be solved by the use of green biocides including nanomaterials which has very low toxicity, environmental acceptability, safety and ease of use etc. Several nanomaterials have been utilized to inhibit the growth of different microorganisms and can be a possible alternative for controlling SRB biofilm and its corrosion. Here, we introduced an environmentally benign approach to use a green biocide; chitosan-ZnO nanocomposite against SRB induced MIC towards carbon steel. The nanoparticles of chitosan and ZnO were prepared independently and treated together to form the chitosan-ZnO nanocomposite. The nanocomposite was synthesized with different percentage of ZnO initial content and characterized by SEM, TEM, FTIR, TGA etc. The average size of chitosan nanoparticles were in between 40-60 nm and it clearly shows the distribution of ZnO NPs in the chitosan nanoparticles matrix. The particles in chitosan-ZnO nanocomposite were found with almost spherical morphology. The electrodes were made of carbon steel S150 was used for all the experiments. S150 carbon steel electrode of exposed area of 8 mm diameter used for the corrosion experiments after hot mounting process followed by polishing and grinding process. The electrodes were incubated with SRB containing media with and without nanocomposites and kept in a shaking incubator at 37° under inert atmosphere. The effect of the chitosan-ZnO nanocomposite on corrosion inhibition was studied by varying the concentrations of nanocomposites under optimized bacterial concentration and experimental conditions. The surface features and the elemental analysis of the biofilm and corrosion product were evaluated by SEM as well as XPS in different time intervals and compared with the control samples. The surface features of the corroded electrodes was investigated by SEM and profilometry after removing the corrosion product by using a simple chemical treatment procedure. The effect of chitosan-ZnO nanocomposite on corrosion behavior of carbon steel against SRB was investigated by electrochemical impedance spectroscopy, corrosion potential, polarization resistance and polarization curve measurements at different time intervals. It was found that the chitosan-ZnO nanocomposite inhibits the SRB biofilm formation and corrosion. The results of the electrochemical analysis showed that the chitosan-ZnO nanocomposite (10% ZnO content) at 250 ppm concentration having highest corrosion inhibition and can be used an effective corrosion inhibition agent against SRB induced MIC. References Wang, H. F., et al. Materials Chemistry and Physics 124, 791-794, (2010).Vanaei, H. R., et al. International Journal of Pressure Vessels and Piping 149, 43-54, (2017). Xu, D. et al. Engineering Failure Analysis 28, 149-159, (2013).