Organic Carbonates as Solvents in Synthesis and Catalysis

Ionic liquids in separations of azeotropic systems - A review

https://ris.utwente.nl/ws/files/6844574/Meindersma05selection.pdf

Selection of ionic liquids for the extraction of aromatic hydrocarbons from aromatic/aliphatic mixtures

Ionic liquids (ILs) can be used to replace conventional solvents in liquid−liquid extractions of aromatic hydrocarbons. An IL-based extraction process requires fewer process steps and less energy consumption, provided that the mass-based aromatic distribution coefficient and/or the aromatic/aliphatic selectivity are higher than those of the current state-of-the-art solvents such as sulfolane. Only a small number of ionic liquids are able to combine higher mass-based distribution coefficients with selectivities comparable to or higher than those of sulfolane. The most suitable ILs from our analysis are [bmim]C(CN)3, [3-mebupy]N(CN)2, [3-mebupy]C(CN)3, and [3-mebupy]B(CN)4. The mass-based distribution coefficients with these four ILs for benzene, toluene, and p-xylene are factors of 1.2−2.5 higher than those with sulfolane, and the aromatic/aliphatic selectivities are up to a factor of 1.9 higher than with sulfolane. Based on the performed analysis, it can be concluded that industrial application of ILs for...

Ionic Liquids for Aromatics Extraction. Present Status and Future Outlook

Ternary liquid-liquid equilibria for mixtures of toluene + n-heptane + an ionic liquid

Wax deposition from Middle East crudes

Retardation of asphaltene precipitation by addition of toluene, resins, deasphalted oil and surfactants

Extraction of aromatics from naphtha reformate using propylene carbonate

Feed-forward neural networks that models the hydrocracking process of Arabian light vacuum gas oil are presented. The input-output data to the neural networks was obtained from actual local refineries. Several network architectures were tried and the networks that best simulate the hydrocracking process were retained. The networks are able to predict yields and properties of products of the hydrocracking unit (e.g. iC4, nC4, light and heavy naphtha, light and heavy ATK, Diesel, etc.). The predictions of yields and properties of various desired and undesired products at different conditions are required by refineries for process optimization, control, design, catalyst selection, and planning. The predictions of the prepared neural networks have been cross validated against data not originally used in the training process. The networks compared well against this new set of data with an average percent error always less than 8.71 for the different products of the hydrocracking unit.

Modeling the hydrocracking process using artificial neural networks

The formation of tight water-in-oil emulsions during production and transport of crude oils is a great problem challenging the petroleum industry. Tremendous research works are directed to understanding the mechanism of formation, stabilization, and controlling of oil field emulsions. This article presents experimental results of some of the factors controlling the formation and stabilization of water-in-crude oil emulsions. In this study, asphaltenes and resins separated from emulsion samples collected from Burgan oil field in Kuwait have been used to study emulsion stability. Model oils of resin to asphaltene ratio of 5:1 and toluene-heptane mixtures have been used to study the effect of oil aromaticity on emulsion stability. Results indicate that at low toluene content (below 20%) or high content (above 40%) less stable emulsions are formed. At a threshold value of 30% toluene, a very tight model oil emulsion is formed. The effect of resins to asphaltene (R/A) ratio on stability of model oil h...

M. A. Fahim

Papers

Wax deposition from Middle East crudes

Retardation of asphaltene precipitation by addition of toluene, resins, deasphalted oil and surfactants

Extraction of aromatics from naphtha reformate using propylene carbonate

Modeling the hydrocracking process using artificial neural networks

Stability of Water-in-Crude Oil Emulsions: Effect of Oil Aromaticity, Resins to Asphaltene Ratio, and pH of Water