The development of green solvents is vital to decrease the environmental impact of separation processes by replacing their more hazardous equivalents, which often lack biodegradability, nontoxicity, and biocompatibility. Nevertheless, the application of green solvents in industry has been limited by the insufficiency of thermophysical data on their mixtures, which is due to low technological maturity and high cost of experimentation. So, there is a mounting interest in using computational chemistry as a predictive methodology. In this work, the liquid densities (ρ) of the binary mixtures of ethyl lactate or cholinium iso-leucinate with water or ethanol were determined at 288.15, 293.15, 298.15, 303.15, or 308.15 K and 0.1 MPa. Then, the calculated excess volumes (VE) were correlated with molar composition using three different methodologies: third-degree polynomials; Redlich–Kister expansions; and a novel approach based on computational chemistry (density functional theory). The standard deviation (σ) of these approaches to experimental data showed that the novel methodology, which relied on calculating molar volumes by combining B3LYP/6-311++G(d) with the integral equation formalism polarizable continuum model, obtained a better description of the binaries (1.18 × 10–8 < σ/m3·mol–1 < 6.56 × 10–8) than third-degree polynomials (1.25 × 10–7< σ/m3·mol–1 < 15.0× 10–7) and Redlich–Kister expansions (3.40 × 10–8 < σ/m3·mol–1 < 8.74 × 10–8). Moreover, this novel methodology was considered to decrease the number of adjustable parameters while, at the same time, providing a more concrete physical meaning to the parameters and enhanced accuracy and predictivity.
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Velho et al. (2024) studied this question.
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