Zhenxu Yang, Dingkai Hu, Qiang Wang*, Yueru Hui, Yingyu Wang and Yanrui Li,
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Separation of Phenolic Compounds in Coal Tar by Using Deep Eutectic Solvent Extraction with Choline-Urea: Based on Phase Equilibrium Experiments and Molecular Mechanism Investigation
The objective of this study was to assess the environmental compatibility and efficacy of deep eutectic solvents (DESs) prepared from choline chloride and urea as a means of extracting phenolic compounds from coal tar. This method was developed with the objective of addressing the limitations and environmental concerns associated with conventional extraction techniques. Initial predictions of extraction efficiency were made using Hansen dissolution parameters (HSPs) and thermodynamic considerations, with subsequent confirmation obtained through liquid–liquid phase equilibrium experiments. The application of quantum chemistry and visualization techniques demonstrated that hydrogen bonding represents the primary interaction between DESs and phenolic compounds. Furthermore, it was observed that the extraction efficiency of phenol, m-toluene, p-toluene, and o-toluene decreased in a sequential manner. The results emphasize the significance of hydrogen bonding in the extraction process and provide practical and theoretical guidance for the utilization of DESs in the sustainable and efficient extraction of phenolic compounds.
期刊介绍:
The Journal of Chemical & Engineering Data is a monthly journal devoted to the publication of data obtained from both experiment and computation, which are viewed as complementary. It is the only American Chemical Society journal primarily concerned with articles containing data on the phase behavior and the physical, thermodynamic, and transport properties of well-defined materials, including complex mixtures of known compositions. While environmental and biological samples are of interest, their compositions must be known and reproducible. As a result, adsorption on natural product materials does not generally fit within the scope of Journal of Chemical & Engineering Data.