Hybrid organic−inorganic metal-halide perovskite materials are an emerging class of materials that could profoundly change the optoelectronic and solar absorber research fields and have far-reaching applications. Unfortunately, the leading solarabsorbing candidates are lead-containing materials and suffer from chemical instability, eventually decomposing, resulting in detrimental long-term environmental concerns. A series of nontoxic group 14 Sn(II)-based hybrid organic−inorganic metal-halide perovskites is investigated using variable-temperature solid-state nuclear magnetic resonance (NMR) spectroscopy to examine their unique phases that appear between 150 and 540 K. Each phase of the MASnX 3 (MA + = CH 3 NH 3 + and X − = Cl − , Br − , or I − ) series is identified and compared to results from quantum chemical calculations of anionic polyhedron clusters. The analysis of the polyhedra about the Sn center is further related to the measured chemical shift anisotropy present when Sn deviates from octahedral symmetry. We also discuss the rapid degradation of pristine MASnI 3 over 2 days studied using in situ 119 Sn NMR spectroscopy. Finally, we report on the 1 H, 13 C, 119 Sn, and 207 Pb NMR structural properties of a Sn/Pb mixed B-site (MASn 0.5 Pb 0.5 I 3 ) perovskite, demonstrating the sensitivity of the chemical shift to B-site substitution.

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The cornerstone of foamy oil behavior during cyclic solvent injection (CSI) is its stability, of which depends on parameters such as oil viscosity, temperature, dissolved gas ratio, pressure decline rate, and dissolved gas (solvent) composition. Although the process has been investigated and analyzed for different parameters in the literature, the optimal conditions for an effective and more economical process (mainly foamy oil stability) has not been thoroughly understood, especially for secondary recovery conditions. In this study, air has been used as an ameliorative to improve foamy oil stability during CSI. Four pressure-depletion tests were performed, each of them consisting of five consecutive cycles. It was observed that increasing pressure-depletion rates increased the formation of foamy oil; however, when pressure-depletion rates were too high, it may have caused a negative effect in the final oil recovery factor by CSI. Injecting air into the sandpack caused an increase in the viscosity of heavy oil, and the subsequent injection of methane as a solvent became more effective in generating a more stable foamy oil, which resulted in obtaining a higher oil recovery factor.

Co-solvents are widely used to improve chemical flooding formulation design, but their partitioning between phases has great impacts on microemulsion phase behavior. Therefore, it is critical to accurately model microemulsion phase behavior with phase partitioning of co-solvents in a compositional chemical flooding simulator, in order to correctly predict oil recovery and better evaluate the performance of the designed formulation. We use the physics based HLD-NAC EOS implemented with the co-solvent partitioning model developed by Biais et al. (1981) and Hirasaki (1982) to model microemulsion phase behavior with cosolvents. The HLD-NAC model can determine microemulsion phase type by correlated phase behavior dependent variables and can calculate the overall interfacial area and sizes of micelle by characterized surfactant properties. To accurately estimate the interfacial area taking into account the contribution of co-solvents, an interfacial pseudophase composed of surfactant and co-solvents is defined. Partitioning coefficients of co-solvents between interfacial pseudophase and bulk pseudophase are experimentally measured. This novel model has only one fitting parameter, which is the tail length (Lsurf) of surfactant mixtures. We used five microemulsion systems to examine the developed approach. Solubilization ratios under a salinity scan of these systems are reproduced. Without using the co-solvent partitioning model, the matched Lsurf is dramatically underestimated for each system due to assuming all co-solvents are adsorbed onto the interface. With the improved model, the matched Lsurf is more physically representing the actual surfactant tail length. Microemulsion compositions predicted by the novel HLD-NAC EOS is in a good agreement with the experimentally measured microemulsions at all phase behavior types from Winsor Type I, through Winsor Type III to Winsor Type II. The results prove the physics based HLD-NAC EOS coupling with the thermodynamic co-solvent phase partitioning model can accurately simulate phase behavior of surfactant/co-solvent/brine/crude oil systems. The novelty of the present work is to exercise the physics-based HLD-NAC EOS to model the phase behavior of the aforementioned systems considering co-solvent partitioning. The new model can be used in compositional chemical flooding reservoir simulation to improve the predictability of surfactant floods.

Summary Foamy oil flow is a commonly encountered drive mechanism in the primary production (depletion of naturally methane-saturated heavy oil) and secondary stage (cyclic gas—mostly methane—injection after primary production). In the former, among other important parameters, pressure depletion rate has been reported to be the most crucial parameter to control the process. In the latter, type and amount of the gas (also described as “solvent”) and application conditions such as soaking time durations and depletion rates are critical. The cornerstone of the foamy oil behavior relies on its stability, which depends on parameters such as oil viscosity, temperature, dissolved gas ratio, pressure decline rate, and dissolved gas (solvent) composition. Although the process has been investigated and analyzed for different parameters in the literature, the optimal conditions for an efficient process (mainly foamy oil stability) has not been thoroughly understood, especially for the secondary recovery conditions (cyclic solvent injection, CSI). In this paper, internal and external gas drive mechanisms for foamy oil performance are reviewed in detail. The optimal conditions of the applications were compiled and listed for different primary production and secondary recovery stages. Combination of methane with other gases as a CSI practice was also discussed to accelerate the process and reduce cost in an effort to improve efficiency. It is reported that combining methane injection with air as a secondary recovery method can save up to 51% of solvent gas.