4.6 Article

Cationic gemini-surfactants based on waste cooking oil as new 'green' inhibitors for N80-steel corrosion in sulphuric acid: A combined empirical and theoretical approaches

期刊

JOURNAL OF MOLECULAR STRUCTURE
卷 1203, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.molstruc.2019.127442

关键词

Sustainable inhibitors; Waste frying oil; Surface morphology; EIS; Gemini cationic surfactants; DFT

资金

  1. Deanship of Scientific Research at King Faisal University, Saudi Arabia [186269]

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The objective of this report is to investigate the inhibition of cationic gemini-surfactants based on waste cooking, as a green source of inhibitors against acidic corrosion of N80-steel. Two Gemini cationic surfactants have been prepared based on waste frying oil with full characterization by different spectral tools (FTIR, H-1 NMR and C-13 NMR), and investigated as sustainable inhibitors for N80-steel corrosion in 1.0 M sulphuric acid. The activities of the prepared Gemini cationic compounds were evaluated from the surface-tension studies. The corrosion protection capacity was evaluated by utilizing electrochemical tools namely; LPR corrosion rate, electrochemical impedance-spectroscopy (EIS) and potentiodynamic-polarization (PDP) methods. The PDP findings demonstrated that these surfactants behaved as mixed-typed inhibitors. The surfactants prohibited N80-steel corrosion at a lower [inhibitor] and supplied an inhibition capacity of 96.48-97.86% in 1 x 10(-3) mol/l. The protection power increased with increasing both [surfactant] and alkyl group length. The surfactants adsorb on N80-steel in the studied corrosive medium through chemisorption interactions and their adsorption followed the adsorption model of Langmuir. Surface morphology observations (FE-SEM and FTIR) suggest that the surfactant species formed a defensive layer on the N80-steel interface. The electronic properties of the prepared surfactants were examined by using DFT calculations (density functional theory). Theoretical findings are consistent with the empirical outcomes. (C) 2019 Elsevier B.V. All rights reserved.

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