Design of industrial wastewater demulsifier by HLD-NAC model
Abstract The chemical method is one of the treatment techniques for the separation of oil–water emulsion systems. The selection of appropriate demulsifiers for each emulsion system is the most challenging issue. Hydrophilic-lipophilic-deviation (HLD) is a powerful semi-empirical model, providing pre...
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| Autores principales: | , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/5e4d91a5bf9d4e65ac4053dd2262d3d4 |
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| Sumario: | Abstract The chemical method is one of the treatment techniques for the separation of oil–water emulsion systems. The selection of appropriate demulsifiers for each emulsion system is the most challenging issue. Hydrophilic-lipophilic-deviation (HLD) is a powerful semi-empirical model, providing predictive tools to formulate the emulsion and microemulsion systems. This work aims to apply HLD to obtain an optimal condition for demulsification of oil-in-water emulsion system—real industrial wastewater—with different water in oil ratios (WOR). Therefore, the oil parameter of the contaminant oil and surfactant parameter for three types of commercial surfactants were calculated by performing salinity scans. Furthermore, the net-average-curvature (NAC) framework coupled with HLD was used to predict the phase behavior of the synthetic microemulsion systems, incorporating solubilization properties, the shape of droplets, and quality of optimum formulation. The geometrical sizes of non-spherical droplets (L d , R d )—as an indicator of how droplet sizes are changing with HLD—were consistent with the separation results. Correlating L d /R d at phase transition points with bottle test results validates the hypothesis that NAC-predicted geometries and demulsification behavior are interconnected. Finally, the effect of sec-butanol was examined on both synthetic and real systems, providing reliable insights in terms of the effect of alcohol for WOR ≠ 1. |
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