Computational prediction of ionic liquid 1-octanol/water partition coefficients

Area of Science:

• Physical Chemistry
• Computational Chemistry
• Materials Science

Background:

• Ionic liquids (ILs) are versatile solvents with tunable properties.
• Accurate prediction of their physicochemical properties, such as the 1-octanol/water partition coefficient (log Kow), is crucial for application development.
• Experimental determination of log Kow can be time-consuming and resource-intensive.

Purpose of the Study:

• To evaluate the efficacy of adaptive bias force-molecular dynamics (ABF-MD) simulations for predicting log Kow of imidazolium-based ionic liquids.
• To assess the potential of this computational approach for the a priori prediction and screening of IL properties.

Main Methods:

• Adaptive bias force-molecular dynamics (ABF-MD) simulations were employed.
• Predicted log Kow values were compared against experimental data for imidazolium-based ILs.

Main Results:

• ABF-MD simulations yielded log Kow predictions in excellent agreement with experimental values.
• The computational method demonstrated high accuracy for the studied ionic liquids.

Conclusions:

• ABF-MD simulations are a reliable computational tool for predicting log Kow of ionic liquids.
• This approach offers a promising strategy for the a priori prediction and high-throughput screening of ionic liquids, including those with specific properties like CO(2)-philicity.