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Updated: Jan 27, 2026

Preparation of Binary and Ternary Deep Eutectic Systems
Published on: October 31, 2019
Computational Design of Natural Deep Eutectic Systems Using COSMO-RS for Ice Control Applications.
Akshat S Mallya1, Priyanka Yadav1, Stephanie Zakhia1
1Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, Minnesota 55414, United States.
This study introduces a computational method to predict Natural Deep Eutectic Systems (NADES) for ice control. Optimized NADES significantly reduce ice formation and fusion enthalpies, offering a greener alternative to traditional methods.
Area of Science:
- Green Chemistry
- Computational Chemistry
- Materials Science
Background:
- Natural Deep Eutectic Systems (NADES) offer sustainable, low-toxicity alternatives in chemistry.
- Current NADES development relies on empirical methods, necessitating optimization for specific applications like ice control.
Purpose of the Study:
- To develop an in silico methodology for prescreening and predicting eutectic compositions of NADES.
- To optimize NADES for effective ice control applications.
Main Methods:
- Utilized conductor-like screening model for real solvents (COSMOS-RS) to predict activity coefficients and binary phase diagrams.
- Employed differential scanning calorimetry (DSC) and low-temperature Raman spectroscopy for experimental validation.
- Analyzed quantum chemical descriptors to identify new prescreening parameters.
Main Results:
- Predicted eutectic compositions of NADES showed significantly reduced enthalpies of fusion (>70%) and ice crystal formation (>50%) compared to pure water.
- Experimental characterization confirmed the anti-icing potential of selected amino acid-sugar alcohol (AA-SA) and sugar-sugar alcohol (SU-SA) NADES.
- Identified hydrogen bond donating moments as a potential new descriptor for NADES prescreening.
Conclusions:
- The in silico methodology effectively predicts NADES eutectic compositions with enhanced ice control properties.
- Developed NADES demonstrate significant potential for sustainable anti-icing applications.
- Quantum chemical descriptors offer new avenues for developing quantitative structure-property relationship (QSPR) models for NADES design.
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