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Insight into the corrosion inhibition of copper in sulfuric acid via two environmentally friendly food spices: Combining experimental and theoretical methods
The food spices of difurfuryl disulfide (DFD) and furfuryl mercaptan (FFM) as corrosion inhibitors for copper in 0.5 M sulfuric acid were investigated via abundant testing methods. The electrochemical tests showed DFD and FFM exhibit excellent corrosion inhibition performance and can suppress both c...
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Published in: | Journal of molecular liquids 2019-07, Vol.286, p.110891, Article 110891 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The food spices of difurfuryl disulfide (DFD) and furfuryl mercaptan (FFM) as corrosion inhibitors for copper in 0.5 M sulfuric acid were investigated via abundant testing methods. The electrochemical tests showed DFD and FFM exhibit excellent corrosion inhibition performance and can suppress both cathodic and anodic reactions for Cu in sulfuric acid. At 298 K, the potentiodynamic polarization test showed that the highest inhibition efficiencies of DFD and FFM were 97.5% and 98.9%, respectively. Surface morphology analysis strongly supports the results of electrochemical measurements. In addition, X-ray photoelectron spectroscopy (XPS) detected the CuS bond. Adsorption of DFD and FFM on copper surface conforms to Langmuir isotherm model. Theoretical calculations are used to delve into the differences in corrosion inhibition performance between DFD and FFM. Finally, all experiments had proven that DFD's corrosion inhibition efficiency is better than that of FFM.
•The DFD exhibits superior corrosion inhibition performance than FFM.•Electrochemical test data indicate the order of inhibition efficiency: DFD > FFM.•The DFD and FFM adsorb on the copper surface in accordance with the Langmuir model.•Theoretical calculations provide in-depth understanding of the experimental results. |
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ISSN: | 0167-7322 1873-3166 |
DOI: | 10.1016/j.molliq.2019.110891 |