Experimental and machine learning approaches reveal density behavior in ionic liquid solutions, indicating strong ion-solvent interactions.
The thermophysical properties of ionic liquids (ILs) in dilute solutions are crucial for their industrial applications. In this study, two allyl-functionalized imidazolium ionic liquids─1-allyl-3-ethylimidazolium dicyanamide ([AEim][DCA]) and 1-allyl-3-ethylimidazolium tetrafluoroborate ([AEim][BF₄])─were synthesized. The densities of their aqueous solutions at molalities ranging from 0.1000 to 1.000 mol·kg⁻¹ were systematically measured at T = (288.15-313.15 K) and p = 0.1 MPa. Furthermore, a machine learning model based on an artificial neural network (ANN) was developed, which successfully predicted the density of the IL-water binary systems (R² = 0.9794). SHAP analysis revealed that concentration is the most important factor influencing density. The apparent molar volume (VΦ) and its infinite dilution value (VΦ∞) were calculated via the Redlich-Meyer equation. The results showed that the value for the [AEim][DCA] system is lower than that for [AEim][BF₄], indicating that the [DCA]⁻ anion exhibits superior hydrophilicity and stronger ion-solvent interactions at infinite dilution. Both systems exhibited positive Av values and negative Bv, suggesting that ion-ion interactions dominate in the dilute aqueous solutions of [AEim][DCA] and [AEim][BF₄], accompanied by a water structure-making effect. The Pitzer equation yielded results were in good agreement with the Redlich-Meyer equation (deviation within 0.55 × 10⁻⁶ m³·mol⁻¹). Moreover, the βM,X⁽⁰⁾-βM,X⁽¹⁾ plot demonstrated that the short-range interaction patterns of the studied ionic liquids resemble those of most inorganic salts.
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Li et al. (2026) studied this question.
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