Recent Progress in Composite Solvents for Chemical Separations

WANG Mingmei; WANG Erqiang

doi:10.3724/j.issn.1674-4969.20260094

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Recent Progress in Composite Solvents for Chemical Separations

更新时间：2026-09-14

- Recent Progress in Composite Solvents for Chemical Separations
- Journal of Engineering Studies Pages: 1-18(2026)
- 作者机构：
  
  1.中国科学院大学化学科学学院，北京 101400
  2.中国科学院大学化学工程学院，北京 101400
- 作者简介：
- 基金信息：
- DOI：10.3724/j.issn.1674-4969.20260094
  CLC： TQ0
- CSTR：32282.14.JES.20260094
- Received：12 June 2026，
  
  Revised：2026-07-22，
  
  Online First：14 September 2026，
- 稿件说明：
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王明媚,王二强.复合溶剂在化工分离中的研究进展[J].工程研究——跨学科视野中的工程,

WANG Mingmei,WANG Erqiang.Recent Progress in Composite Solvents for Chemical Separations[J].Journal of Engineering Studies,
王明媚,王二强.复合溶剂在化工分离中的研究进展[J].工程研究——跨学科视野中的工程, DOI：10.3724/j.issn.1674-4969.20260094. CSTR： 32282.14.JES.20260094.

WANG Mingmei,WANG Erqiang.Recent Progress in Composite Solvents for Chemical Separations[J].Journal of Engineering Studies, DOI：10.3724/j.issn.1674-4969.20260094. CSTR： 32282.14.JES.20260094.

摘要

复合溶剂通过组分间的协同作用实现对溶剂性质的灵活调控，在萃取分离、吸收分离等化工过程中表现出优于单一溶剂的综合性能。本文综述了复合溶剂的基本特征及其在萃取分离和吸收分离中的研究进展，重点分析了溶剂极性调控、组分协同作用及其对分离性能的影响规律，并总结了基于极性参数、第一性原理计算、机器学习和多尺度模拟的复合溶剂设计方法。在此基础上，对复合溶剂设计与应用的发展现状及未来趋势进行了讨论，以期为高性能分离溶剂的开发与应用提供参考。

Abstract

Composite solvents

formulated by blending two or more functional components in tailored ratios

have become a central strategy in chemical separation. Blending allows intermolecular interactions

polarity

and thermodynamic equilibria to be tuned in ways that no pure solvent can match. Compared with single solvents

ionic liquids

and deep eutectic solvents—each constrained by limited adjustable handles—the compositional space of composite solvents is far richer and is directly accessible to engineering. This review summarizes recent progress on extraction and absorption separations

the design methodology that links molecular descriptors to bulk performance

and the bottlenecks that prevent industrial uptake.

In extraction

sulfolane-based composite solvents remain the benchmark for aromatic/aliphatic separation; COS co-solvents markedly improve aromatic selectivity

while SED-based systems replace sulfolane to ease toxicity concerns. DMF-CY11 composites give low solubility and high partition coefficients for aromatics from lube-oil raffinate. For phenol recovery from coal-tar oil

furfural-KSCN and DMF-KSCN composites achieve distribution coefficients an order of magnitude above single solvents. Hybrid systems combining an extractant

a polar diluent and an inorganic salt markedly improve separation factors and avoid emulsification

as exemplified by DBP-sulfolane-inorganic salt systems for coal-tar phenol recovery.

In absorption

MDEA-piperazine hybrid solvents combine the high capacity of MDEA with the rapid kinetics of piperazine and have been adopted in large-scale CO

capture; MEA-MDEA-piperazine ternary solvents extend the workable loading range. Amine mixtures of AMP with TETA or piperazine derivatives exploit steric and catalytic effects. Sulfolane-based physical-chemical hybrids

such as BHEP-sulfolane and PC-BHEP

target both CO

and H

S with tailorable heat duties. For VOC and BTEX absorption

hydroxyl composite solvents substantially improve capacity and stability versus single glycol ethers.

Design methodology is shifting from empirical screening to multi-scale integration. Polarity parameters (Kamlet-Taft

Hansen

dielectric constant) provide a first-pass handle. COSMO-RS-derived

-moment descriptors predict capacity and selectivity directly from quantum-chemically computed surface charge and identify polar and hydrogen-bonding regions as the dominant contributors. Machine-learning models trained on high-throughput COSMO-RS data accelerate the search across vast compositional spaces and have already guided the discovery of several high-performance separation solvents. Multi-scale molecular dynamics and quantum calculations finally revea

l synergistic mechanisms at the molecular level and link composition to macroscopic selectivity.

Three bottlenecks remain. Synergistic mechanisms are still described qualitatively and quantitative descriptors that unambiguously define a composite are missing. Data-driven screening depends on scarce

high-quality experimental data. Green and sustainable assessments (toxicity

biodegradability

energy intensity) are rarely integrated into the design loop. Future work should couple high-throughput experiments

machine learning

multi-scale simulation and life-cycle assessment within closed platforms

expand compositional libraries toward IL-DES hybrids and bio-derived components

share open benchmark datasets

and embed process-intensification criteria into solvent selection

so as to enable the rational design of next-generation composite solvents for green

low-carbon separation processes.

关键词

Keywords

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