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Investigation of Potential Azeotrope Breakers Using DFT and COSMO Approach
Anantharaj Ramalingam1, Ramesh Kumar Gurunathan2, Pratheeba Chanda Nagarajan2
1Department of Chemical Engineering, SSN College of Engineering, Rajiv Gandhi Salai (OMR), Kalavakkam, Chennai 603110, Tamil Nadu, India.
This study explores ionic liquids for butanol-water separation. Computational methods identified promising entrainers to break azeotropes, aiding in efficient separation processes.
Area of Science:
- Physical Chemistry
- Computational Chemistry
- Materials Science
Background:
- Ionic liquids (ILs) are tunable solvents with potential applications in separation processes.
- Understanding the physicochemical properties of ILs is crucial for designing effective separation agents.
- The butanol-water azeotrope presents a challenge in separation and purification.
Purpose of the Study:
- To investigate various cation-anion combinations of ionic liquids for their potential as entrainers.
- To predict the performance of ionic liquids in the butanol-water system using computational methods.
- To identify a feasible entrainer for breaking the butanol-water azeotrope.
Main Methods:
- Density Functional Theory (DFT) calculations for quantum chemical parameters.
- COSMO-RS (Conductor-like Screening Model for Real Solvents) for sigma profiles and potentials.
- Activity coefficient at infinite dilution calculations for the butanol-water system.
Main Results:
- Evaluated COSMO volume and DFT-derived properties (HOMO/LUMO energies, energy gap, hardness, softness, electronegativity, electrophilicity, chemical potential) for diverse ILs.
- Generated sigma profiles and potentials for selected cations and anions using COSMO-RS.
- Determined activity coefficients at infinite dilution for the butanol-water system to assess nonideality.
Conclusions:
- Computational screening identified specific ionic liquid combinations with favorable properties for butanol-water separation.
- A feasible entrainer was proposed for breaking the butanol-water azeotrope, demonstrating the utility of the applied computational approach.
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