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基于概念密度泛函理论的腐蚀抑制预测新型 QSPR 模型。

New QSPR model for prediction of corrosion inhibition using conceptual density functional theory.

机构信息

Área Académica de Química, Universidad Autónoma del Estado de Hidalgo, Ciudad del Conocimiento, km 4.5 Carretera Pachuca-Tulancingo, 42184, Mineral de la Reforma Hidalgo, Mexico.

出版信息

J Mol Model. 2022 Jul 29;28(8):238. doi: 10.1007/s00894-022-05240-6.

Abstract

The relationship between structure and corrosion inhibition of a series of twenty-eight quinoline and pyridine derivatives has been established through the investigation of quantum descriptors calculated with PBE/6-311 +  + G** method. A quantitative structure-property relationship (QSPR) model was obtained by examining these descriptors using a genetic algorithm approximation method based on a multiple linear regression analysis. The results indicate that the efficiency of corrosion inhibitors is strongly associated with hardness (η), minimal electrostatic potential (ESP), and volume (V) descriptors. Furthermore, the validity of the proposed model is corroborated by an adsorption study on an iron surface Fe(110).

摘要

通过使用 PBE/6-311 +  + G** 方法计算量子描述符,研究了二十八种喹啉和吡啶衍生物的结构与缓蚀性能之间的关系。通过使用基于多元线性回归分析的遗传算法近似方法检查这些描述符,获得了定量构效关系(QSPR)模型。结果表明,缓蚀剂的效率与硬度(η)、最小静电势(ESP)和体积(V)描述符密切相关。此外,通过在铁表面 Fe(110)上进行吸附研究进一步验证了所提出模型的有效性。

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