EFFECT OF SYZYGIUM CUMINI LEAF EXTRACT AS A GREEN CORROSION INHIBITOR ON API 5L CARBON STEEL IN 1M HCl

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Abstract

Corrosion in API 5L steel under 1M HCl is a common issue; hence, creating a more effective and naturally-based inhibitor is critical. In this research, Syzygium Cumini leaf extract (SCLE) was used as a new green corrosion inhibitor under acidic conditions. The inhibition properties of the novel cumini extract were thoroughly characterized using potentiodynamic polarization (PDP), electrochemical impedance spectroscopy (EIS), Fourier-transform infrared spectroscopy (FTIR), and atomic force microscope (AFM). The results show that the cumini inhibitor has excellent corrosion inhibition with 93 % inhibition efficiency. The adsorption behavior of the inhibitor follows the Langmuir Adsorption Isotherm due to the nearness of R2 to unity. The potentiodynamic and electrochemical measurements demonstrate the mixed type of corrosion inhibitor. Thermodynamic calculation of ΔGads is – 18.41 kJ mol-1 showing the physical adsorption process between the inhibitor and metals. Further inspection of ΔHads at ‒58.93 kJ mol-1 considers releasing energy during adsorption. The FTIR results agree with the increased growth of passive layers due to the adsorption of polyphenol and flavonoids on metals. Remarkably, the adsorption peak at 3266.59 cm-1 corresponds to the adsorption of –OH. The peak at 1612.56 and 1698.4 cm-1 is attributed to C=C and C=O functional groups. The above functional groups serve as adsorption centers to reduce the corrosion effect. The surface treatment of AFM indicated a good relationship with the functional group characterization and confirmed the significant corrosion rate reduction. This work can be used as a benchmark to develop a natural plant as a corrosion inhibitor

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Riastuti, R., Mashanafie, G., Rizkia, V., Maksum, A., Prifiharni, S., Kaban, A., … Soedarsono, J. (2022). EFFECT OF SYZYGIUM CUMINI LEAF EXTRACT AS A GREEN CORROSION INHIBITOR ON API 5L CARBON STEEL IN 1M HCl. Eastern-European Journal of Enterprise Technologies, 6(6–120), 30–41. https://doi.org/10.15587/1729-4061.2022.267232

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