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Toward high-performance associative extraction by forming deep eutectic solvent: A component pairing and mechanism study

Journal 2023 · IF 4.7 · 发表于 2023 年 3 月 5 日
作者: Linsheng Wang,Yulou Cui,Jiangtao Li,Zhen Song,Hongye Cheng,Zhiwen Qi
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摘要

Associative extraction by selectively forming deep eutectic solvent (DES) with the target solute exhibits high performance toward many hard-to-separate systems; however, selecting a proper associative extractant for a specific task is challenging as high extraction efficiency and forming liquid DES should be satisfied simultaneously. In this work, a systematic component pairing method is proposed to rationally select suitable hydrogen bond acceptors (HBA) for associative extraction, which includes three steps: collecting HBA candidates, theoretical pairing from extraction potential evaluation and solid–liquid phase behavior estimation, and experimental validation. For two exemplary separation cases, (i.e., detergent range alcohol-alkane mixture and phenol-toluene mixture), suitable HBAs with high extraction performance and wide liquid operating window are successfully selected, demonstrating the reliability of the method. Hydrogen bonding interaction drives the selective formation of DES with the target solute, and the interaction strength depends on the solute structure, which in turn determines the selection of suitable HBAs.

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