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Updated: Jun 1, 2025

Preparation of Binary and Ternary Deep Eutectic Systems
Published on: October 31, 2019
Deep Eutectic Solvents Meet Non-Aqueous Cosolvents: A Modeling and Simulation Perspective-A Tutorial Review.
Leon de Villiers Engelbrecht1, Narcis Cibotariu2, Xiaoyan Ji1
1Division of Energy Science, Energy Engineering, Luleå University of Technology, 97187 Luleå, Sweden.
Molecular modeling advances the understanding of deep eutectic solvents (DESs) when mixed with cosolvents beyond water. This review details how these simulations reveal structural, transport, and thermodynamic properties for novel solvent design.
Area of Science:
- Chemistry
- Materials Science
- Computational Science
Background:
- Deep eutectic solvents (DESs) offer tunable properties for green chemistry, pharmaceuticals, and energy storage.
- Mixing DESs with cosolvents like ethanol or acetonitrile modifies their characteristics.
- Water is the most studied cosolvent, but non-aqueous mixtures are crucial for specific applications.
Purpose of the Study:
- To provide a comprehensive overview of molecular modeling studies on DES-cosolvent mixtures (excluding water).
- To highlight the role of computational techniques in understanding DES behavior in non-aqueous mixtures.
- To discuss recent advancements, challenges, and future directions in this emerging field.
Main Methods:
- Quantum mechanical calculations
- Molecular dynamics simulations
- Analysis of structural organization, transport, phase, and thermodynamic properties
Main Results:
- Molecular modeling elucidates the complex behavior of DESs in various cosolvent mixtures.
- Studies reveal insights into structural organization, transport phenomena, and phase equilibria.
- Computational approaches enable the prediction of thermodynamic properties for tailored solvent design.
Conclusions:
- Modern molecular modeling is essential for understanding DES-cosolvent systems at a molecular level.
- This understanding facilitates the design of novel solvent mixtures with specific properties.
- Further research in computational modeling will drive innovation in DES applications.
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