Understanding the origin of high corrosion inhibition efficiency of bee products towards aluminium alloys in alkaline environments
Jacek Ryl , Joanna Wysocka , Mateusz Cieslik , Husnu Gerengi , Tadeusz Ossowski , Stefan Krakowiak , Paweł Niedziałkowski
AbstractVarious bee products were found to be efficient corrosion inhibitors of aluminium in different environments. In particular, bee pollen was found to be highly effective in alkaline electrolytes, yet its highly complex composition and possible synergistic interactions hinder determination of the compounds acting as active corrosion inhibitors. The main purpose of the following work is to investigate the effect of solvents used for pollen extraction process on the corrosion inhibition of AA5754 alloy in alkaline environment. Both infrared and mass spectroscopies as well as chromatographic analysis were used to determine differences in the composition of each obtained extract. The inhibition efficiency (IE%) of each extract was determined by using the potentiodynamic polarization and impedance studies. The highest IE%, exceeding 90% at 10 gL-1, was recorded for the water/ethanol extract. Most importantly, it has been found that the dichloromethane extract containing less polar compounds enhanced the corrosion rate at low bee pollen concentrations, and offered lower inhibition efficiency at the concentrations above 10 gL-1. The adsorption isotherms were drawn based on dynamic impedance spectroscopy in galvanostatic mode (g-DEIS), while the measurements carried out at elevated temperatures allowed the construction of Arrhenius plots and, consequently, the confirmation of the physical mechanism of adsorption.
|Journal series||Electrochimica Acta, ISSN 0013-4686, (A 40 pkt)|
|Publication size in sheets||1.75|
|Keywords in English||Corrosion inhibition, aluminium alloys, green chemistry, surface analysis, adsorption, dynamic impedance spectroscopy|
|Score|| = 40.0, 15-04-2019, ArticleFromJournal|
= 40.0, 15-04-2019, ArticleFromJournal
|Publication indicators||: 2017 = 1.101; : 2017 = 5.116 (2) - 2017=4.857 (5)|
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