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Superparamagnetic nanoparticles (SPNs) have been considered as one of the most studied nanomaterials for subsurface applications, including in enhanced oil recovery (EOR), due to their unique physicochemical properties. However, a comprehensive understanding of the effect of surface functionalization on the ability of the nanoparticles to improve secondary and tertiary oil recoveries remains unclear. Therefore, investigations on the application of bare and surface-functionalized SPNs in EOR using a sand pack were carried out in this study. Here, the as-prepared SPNs were functionalized using oleic acid (OA) and polyacrylamide (PAM) to obtain several types of nanostructure architectures such as OA-SPN, core–shell SPN@PAM, and SPN-PAM. Based on the result, it is found that both the viscosity and mobility of the nanofluids were significantly affected by not only the concentration of the nanoparticles but also the type and architecture of the surface modifier, which dictated particle hydrophilicity. According to the sand pack tests, the nanofluid containing SPN-PAM was able to recover as much as 19.28% of additional oil in a relatively low concentration (0.9% w/v). The high oil recovery enhancement was presumably due to the ability of suspended SPN-PAM to act as a mobility control and wettability alteration agent and facilitate the formation of a Pickering emulsion and disjoining pressure.

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Mathematical modeling of olefin polymerization processes has advanced significantly, driven by factors such as the need for higher-quality end products and more environmentally-friendly processes. The modeling studies have had a wide scope, from reactant and catalyst characterization and polymer synthesis to model validation with plant data. This article reviews mathematical models developed for olefin polymerization processes. Coordination and free-radical mechanisms occurring in different types of reactors, such as fluidized bed reactor (FBR), horizontal-stirred-bed reactor (HSBR), vertical-stirred-bed reactor (VSBR), and tubular reactor are reviewed. A guideline for the development of mathematical models of gas-phase olefin polymerization processes is presented.

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