Aqueous biphasic systems (ABS) based on ethyl lactate are novel green solvent systems that are biorenewable and biodegradable with the potential to replace currently used hazardous organic solvents. Models to correlate and predict binodal curves of these systems are crucial for the design of separation processes but are currently nonexistent. Here, we report the development of two empirical models based on Merchuk’s equation and the Effective Excluded Volume model for ABS composed of ethyl lactate, water and a salt (K3PO4, K2HPO4, K2CO3, Na3C6H5O7, Na2C4H4O6, Na2C4H4O4, K2S2O3, Na2S2O3 and (NH4)2S2O3). Additionally, the use of Artificial Neural Networks (ANN) as a tool to predict binodal curves was explored. An ANN composed of tansig transfer function and five neurons was built using three inputs: mole fraction of salt, molar Gibbs energy of hydration of the salt cation and anion. Furthermore, Fourier-transform infrared-attenuated total reflection spectroscopy was used to reveal the molecular interactions which were used to explain binodal data.
Original languageEnglish
Pages (from-to)1742-1755
Number of pages14
JournalChemical Engineering Communications
Issue number10
Early online date13 Nov 2022
Publication statusPublished - Oct 2023

Bibliographical note

Copyright © 2022, The Author(s). Published with license by Taylor and Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


  • General Chemical Engineering
  • General Chemistry


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