Organically modified nano-clay facilitates pour point depressing activity of polyoctadecylacrylate

Yao, Bo; Li, Chuanxian; Sjöblom, Johan; Zhang, Ying; Norrman, Jens; Paso, Kristofer; Xiao, Zuoqu

doi:10.1016/j.fuel.2015.10.114

Cited by 130 publications

(80 citation statements)

References 28 publications

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“…Interlocking among macro-crystals is spatially hindered by the presence of micro-crystalline crystallites. This mechanism is similar to the effect of recently introduced pour point depressant employing dispersible micro-and nano-particles [29][30][31][32][33][34] . As a result, the platelet-like wax crystals appear as shorter particles, having a maximum length of 10 m and aspect ratio around 5:1, about half of the aspect ratio value found in the 5 wt% macro-crystalline wax without micro-crystalline wax.…”

Section: Cross Polarized Microscopysupporting

confidence: 77%

Influence of Microcrystalline Wax on the Properties of Model Wax-Oil Gels

et al. 2018

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The influence of micro-crystalline wax addition upon the rheological properties of model wax-oil gels is investigated. Addition of less than 1 wt% micro-crystalline wax to a model oil consisting of 5 wt% macro-crystalline wax in dodecane shows no significant impact on the WAT and gelation temperature. Beyond 1 wt% added micro-crystalline wax, increases in WAT and gelation temperature are observed, and are attributable to the higher crystallization temperature of the micro-crystalline wax. The effect of micro-crystalline wax addition upon the WAT and gelation temperature are shown to be attributed to merely overlapping compositions of macro-and microcrystalline wax. However, a substantive effect of micro-crystalline wax addition is observed on the yield stress. Addition of 0.13 wt% micro-crystalline wax reduces the yield stress of waxy oil model from 238.0 to 22.5 Pa. Addition of 0.5 wt% micro-crystalline wax decreases the yield stress to 5.4 Pa, which is close in value to the yield stress of neat 5 wt% micro-crystalline wax gel.2 Microscopic images reveal two mechanisms leading to formation of a weak mixed wax gels. At low to medium addition of micro-crystalline wax, micro-crystalline crystallites formed during cooling provide nucleation sites for subsequent precipitation of macro-crystalline wax. Macrocrystalline wax crystals formed in contact with micro-crystalline crystallites are smaller in size and the growth is localized, in comparison to neat macro-crystalline wax. Modified macro-crystalline wax precipitation leads to uneven dispersion of the macro-crystalline crystals in the liquid phase.At high concentration, micro-crystals form throughout the sample prior to precipitation of macrocrystalline wax. Hence, only small and discrete space remains for macro-crystalline crystals to grow, forming small crystals. Interlocking among macro-crystals is spatially hindered by the presence of micro-crystalline crystallites. In this condition, the system completely behaves as a micro-crystalline gel. This investigation provides a plausible mechanistic account for the known gel weakening activity of micro-crystalline wax.

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Section: Cross Polarized Microscopysupporting

confidence: 77%

Influence of Microcrystalline Wax on the Properties of Model Wax-Oil Gels

et al. 2018

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“…Nanoparticle-PPD composites have been stated to function in a similar way, as these can lead to the formation of compact and amorphous aggregates by serving as nucleation sites. 29,42 The action of PPDs with impurities from ultrasonic disintegration is not directed towards performance enhancement in this case, as the PPDs have not been chemically bound on the impurities. In conclusion, the presence of impurities from ultrasonic disintegration might facilitate wax nucleation, but at the same time no significant influence on WAT and gelation point could be detected.…”

Section: Influence Of Impurities From Ultrasonic Disintegrationmentioning

confidence: 99%

Influence of wax inhibitor molecular weight: Fractionation and effect on crystallization of polydisperse waxes

Ruwoldt¹,

Kurniawan

Sørland³

et al. 2019

Journal of Dispersion Science and Technology

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The molecular weight distribution of four wax inhibitors was modified by either stepwise precipitation or ultrasonic disintegration, and the effect of the obtained inhibitor fractions on wax crystallization was studied. Stepwise precipitation yielded narrower molecular weight distributions as measured by size exclusion chromatography (SEC), whereas ultrasonic disintegration reduced the average molecular weight and increase the polydispersity index. The polymer hydrodynamic radius was mapped using nuclear magnetic resonance (NMR), and showed similar trends as SEC measurements. Wax appearance temperature (WAT) and gelation temperature of three model oils and one crude oil were tested using differential scanning calorimetry (DSC) and rheometry. Changes in molecular weight could improve as well as diminish WAT depression. Waxy gelation temperature showed similar trends as WAT measurements, but the influence of inhibitor molecular weight was more pronounced. The largest change in gelation temperature was measured for the lowest molecular weight fractions

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“…During the operation of long-distance crude oil pipelines, the friction along the pipeline is affected by factors such as the pipe diameter, oil viscosity, and pipe flow. The change in the pipe diameter is mainly due to the waxing of the pipe wall, which leads to the reduction in the effective diameter of the pipe and the loss of a greater amount of kinetic energy under the same flow rate (Yao et al 2016). The viscosity of the oil is related to the temperature and flow rate (shearing force) of the oil in the pipe, and it is difficult to calculate due to the nonlinearity of the oil temperature along the pipeline.…”

Section: Introductionmentioning

confidence: 99%

Standard friction prediction model of long-distance hot oil pipelines

Yao

et al. 2020

Pet. Sci.

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We developed a predictive model for the pipeline friction in the 520-730 m 3 /h transmission range using the multi-layerperceptron-back-propagation (MLP-BP) method and analyzing the unit friction data after the pigging of a hot oil pipeline. In view of the shortcomings of the MLP-BP model, two optimization methods, the genetic algorithm (GA) and mind evolutionary algorithm (MEA), were used to optimize the MLP-BP model. The research results were applied to the standard friction prediction of three sections of a hot oil pipeline. After the GA and MEA optimizations, the average errors of the three sections were 0.0041 MPa for the GA and 0.0012 MPa for the MEA, and the mean-square errors were 0.083 and 0.067, respectively. The MEA-BP model prediction results were characterized by high precision and small dispersion. The MEA-BP prediction model was applied to the analysis of the wax formation 60 and 90 days after pigging. The analysis results showed that the model can effectively guide pipe pigging and optimization. There was little sample data for the individual transmission and oil temperature steps because the model was based on actual production data modeling and analysis, which may have affected the accuracy and adaptability of the model.

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Organically modified nano-clay facilitates pour point depressing activity of polyoctadecylacrylate

Cited by 130 publications

References 28 publications

Influence of Microcrystalline Wax on the Properties of Model Wax-Oil Gels

Influence of Microcrystalline Wax on the Properties of Model Wax-Oil Gels

Influence of wax inhibitor molecular weight: Fractionation and effect on crystallization of polydisperse waxes

Standard friction prediction model of long-distance hot oil pipelines

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