A novel method to fabricate micromodels with varying depth (2.5-D) was developed, which allows more realistic investigation on flow in natural 3-D porous media.

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It is well known that the oil recovery efficiency of chemical EOR depends on microemulsion phase behavior and interfacial tension (IFT). The surfactants needed to obtain good phase behavior and ultra-low IFT vary greatly with oil characteristics and reservoir conditions. Hence, it is often necessary to test many surfactant formulations before finding a highly effective one. Based on both sound principles and extensive experience, one would expect to find a relationship between the optimum surfactant structure, the oil characteristics, the brine, and the temperature. Salager's equation (Salager et al., 1979, Anton et al., 2008 shows it is possible to correlate some of these variables to classical surfactant structure. We now have many new surfactants with widely different structures and many more good formulations with a wider range of oils, temperature and so forth. Thus, it becomes imperative to study the underlying trend and to identify the most important variables affecting the optimum surfactant structure. A new correlation has been developed using an extensive data set taking into account the effect of propylene oxide number (PON), ethylene oxide number (EON), temperature, brine salinity and the equivalent alkane carbon number (EACN) of the oil. The new correlation will help in identifying the most important variables and also to improve our understanding of the relationship among variables affecting optimum surfactant structure. In particular, the new equation can be used to predict the optimum carbon number of the surfactant hydrophobe. Results show that larger hydrophobes are needed as either the temperature or the equivalent alkane carbon number (EACN) of the oil increases. The surfactant formulations used for this study include mixtures of sulfate, sulfonate, carboxylate and non-ionic surfactants. This is a new and highly significant advance in the optimization of chemical EOR processes that will greatly reduce the time and cost of the effort required to develop a good formulation as well as to improve its performance.

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Superparamagnetic CuFeO2 nanoparticles were prepared and characterized by XRD, SEM, TEM, FRIR spectroscopy, and vibrating sample magnetometry techniques. The catalytic activity of CuFeO2 nanoparticles was investigated in the one‐pot, three‐component reaction of 2‐aminopyridines, aldehydes, and alkynes using citric acid–dimethylurea melt as a green solvent. An array of imidazo[1,2‐a]pyridines were obtained in good to excellent yields. The catalytic system can be successfully reused six times with keeping its catalytic performance.

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