Bi-fractal and bi-Gaussian theories to evaluate impact of polythiophene-coated Fe3O4 nanoparticles on asphaltene precipitation and surface topography

• Published in: Fuel (Guildford) 2020-07, Vol.272, p.117535, Article 117535
• Main Authors: Tazikeh, Simin, Sayyad Amin, Javad, Zendehboudi, Sohrab, Dejam, Morteza, Chatzis, Ioannis
• Format: Article
• Language: English
• Subjects: Asperity; Asphaltenes; Atomic force microscopy; Bi-fractal; Bi-Gaussian; Fractal geometry; Fractals; Glass substrates; Imaging techniques; Iron oxides; Kurtosis; Nanoparticles; Oil; Parameters; Polythiophene; Statistical methods; Statistical parameters; Statistics; Topography; Topography alteration; Wettability
• ISSN: 0016-2361; 1873-7153
• DOI: 10.1016/j.fuel.2020.117535

[Display omitted] •Polythiophene-coated Fe3O4 nanoparticles are utilized to inhibit asphaltene precipitation.•Effect of nanoparticles on inhibition of asphaltene precipitation and surface topography are analysed.•Hybridized bi-Gaussian and bi-fractal theories for investigation of asphaltene precipitation and inhibition are introduced.•Fractal theory is more precise and reliable than bi-Gaussian and statistical methods.•Asphaltenes are adsorbed more on nanoparticles in heavy oil, compared to light oil. Use of nanoparticles can effectively inhibit asphaltene precipitation. The present study aims to explore the role of polythiophene-coated Fe3O4 nanoparticles in both asphaltene precipitation and surface topography alteration. Topography information of the surface is obtained through employing atomic force microscopy (AFM) imaging technique. Fractal theory, Gaussian theory, and statistical parameters (e.g., skewness and kurtosis parameters) are used to analyze the surface topography in the presence and absence of nanoparticles. The mono-fractal theory does not adequately describe the irregularity of the surface. Thus, the bi-fractal approach is utilized for investigating the topography alteration of the glass substrate as a result of asphaltene precipitation in the presence and absence of nanoparticles in both light and heavy oil samples. In this theory, the asperity of the surface is divided into two categories: micro- and macro-asperity; the fractal dimensions are calculated for each surface separately. Also, this work employs the bi-Gaussian theory for the first time to study characteristics of a surface that consists of summits. The results of the bi-Gaussian theory are in acceptable agreement with those obtained using the bi-fractal theory. It is found that nanoparticles greatly affect the surface topography. The results also confirm that asphaltene can be adsorbed more on nanoparticles in heavy synthetic oil, compared to light synthetic oil. The fractal theory is more accurate than the bi-Gaussian and statistical approaches as the fractal theory considers all scales/dimensions while other methods take into account only the height of asperity. According to the modeling results, the nanoparticles have potential to considerably lower asphaltene precipitation. This study can provide useful guidelines/tips for inhibiting the wettability alteration of the surface upon asphaltene precipitation over production and transportation processes while using nanoparticl