Application of quercetin as a green inhibitor to prevent mild steel corrosion in the petroleum industry: Experimental and modelling techniques

IF 2.7 Q2 Chemistry Chemical Data Collections Pub Date : 2024-02-06 DOI:10.1016/j.cdc.2024.101125

J. Saranya , K. Vagdevi , B. Jyothirmai , N. Anusuya , F. Benhiba , I. Warad , A. Zarrouk

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Abstract

Quercetin (QT) is found to be a green source of anti-corrosion additive for M-S protection in 0.5 M sulfuric solution. Weight loss, surface studies, atomic absorption spectroscopy, potentiodynamic polarization (PP), impedance spectroscopy (EIS), - more especially, scanning electron microscopy combined with energy dispersive spectroscopy SEM/EDS—and simulation studies were among the methods used to evaluate the efficacy of corrosion inhibition. With 1000 ppm of the inhibitor at 303 K, the weight loss trials had the highest inhibition effectiveness of 96.8 % which obeyed Langmuir adsorption isotherm. The inhibitor QT is represented as mixed-type as per polarization studies. Scanning electron microscopy test results showed the lesser degradation of the lower M-S surface in 0.5 M H₂SO₄ solution at 1000 ppm QT. Moreover, modelling studies employing density functional theory (DFT) and molecular dynamics (MD) showed that the green inhibitor QT adsorbed on the M-S surface and formed a barrier on the metal surface.

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在石油工业中应用槲皮素作为绿色抑制剂防止低碳钢腐蚀：实验和建模技术

研究发现，槲皮素（QT）是一种绿色来源的防腐蚀添加剂，可用于 0.5 M 硫酸溶液中的 M-S 保护。评估缓蚀效果的方法包括失重、表面研究、原子吸收光谱、电位极化（PP）、阻抗光谱（EIS）--尤其是扫描电子显微镜结合能量色散光谱法（SEM/EDS）--以及模拟研究。在 303 K 温度下使用 1000 ppm 的抑制剂时，失重试验的抑制效果最高，达到 96.8%，符合 Langmuir 吸附等温线。根据极化研究，抑制剂 QT 属于混合型。扫描电子显微镜测试结果表明，在 0.5 M H2SO4 溶液中，当 QT 的浓度为 1000 ppm 时，下 M-S 表面的降解程度较低。此外，利用密度泛函理论（DFT）和分子动力学（MD）进行的建模研究表明，绿色抑制剂 QT 吸附在 M-S 表面，并在金属表面形成屏障。

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来源期刊

Chemical Data Collections Chemistry-Chemistry (all)

CiteScore

6.10

自引率

0.00%

发文量

169

审稿时长

24 days

期刊介绍： Chemical Data Collections (CDC) provides a publication outlet for the increasing need to make research material and data easy to share and re-use. Publication of research data with CDC will allow scientists to: -Make their data easy to find and access -Benefit from the fast publication process -Contribute to proper data citation and attribution -Publish their intermediate and null/negative results -Receive recognition for the work that does not fit traditional article format. The research data will be published as ''data articles'' that support fast and easy submission and quick peer-review processes. Data articles introduced by CDC are short self-contained publications about research materials and data. They must provide the scientific context of the described work and contain the following elements: a title, list of authors (plus affiliations), abstract, keywords, graphical abstract, metadata table, main text and at least three references. The journal welcomes submissions focusing on (but not limited to) the following categories of research output: spectral data, syntheses, crystallographic data, computational simulations, molecular dynamics and models, physicochemical data, etc.