Optimization of mild steel corrosion inhibition by water hyacinth and common reed extracts in acid media using factorial experimental design
Aquatic macrophytes biomasses provide an opportunity of using their unwanted biomasses that cause ecological disturbance as green corrosion inhibitors. The extracts of water hyacinth (Eichhornia crassipes) and common reed (Phragmits australis) were prepared and assessed, for mild steel corrosion inh...
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Veröffentlicht in: | Green chemistry letters and reviews 2022-01, Vol.15 (1), p.216-232 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Aquatic macrophytes biomasses provide an opportunity of using their unwanted biomasses that cause ecological disturbance as green corrosion inhibitors. The extracts of water hyacinth (Eichhornia crassipes) and common reed (Phragmits australis) were prepared and assessed, for mild steel corrosion inhibition. The inhibitive effect has been investigated by electrochemical impedance spectroscopy and potentiodynamic polarization techniques. Increasing aquatic and ethanolic extract concentration of both plant extracts increased the inhibition efficiency (% IE). The maximum IE was recorded 86.8 and 89.6% for ethanolic extracts of water hyacinth and common reed. The corrosion current density (i
corr
) was recorded as 0.534 and 0.369 mA cm
−2
for water hyacinth and common reed, respectively, at the maximum concentration. Theoretical fitting of isotherms, Langmuir, Florry-Huggins, and kinetic-thermodynamic models were analyzed to clarify the nature of adsorption behaviour. The % IE of plants extract for mild steel corrosion was evaluated and optimized by 2
(3)
full factorial experimental design. Three factors have been studied namely: extraction method, pH and extract dose. The optimum conditions were at low pH and high plant extract dose concentration especially with ethanolic extraction. The validation models were calculated with R
2
≥ 0.986. The effectiveness of the investigated green inhibitors was also verified using the response surface methodology (RSM). |
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ISSN: | 1751-8253 1751-7192 |
DOI: | 10.1080/17518253.2022.2032844 |