Aqueous biphasic systems based on ethyl lactate: Molecular interactions and modelling


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.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Chemical Engineering & Applied Chemistry
College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > Energy and Bioproducts Research Institute (EBRI)
College of Engineering & Physical Sciences > Aston Institute of Materials Research (AIMR)
College of Engineering & Physical Sciences > Aston Advanced Materials
Additional Information: 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 (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Uncontrolled Keywords: General Chemical Engineering,General Chemistry
Publication ISSN: 1563-5201
Last Modified: 14 Jun 2024 07:27
Date Deposited: 23 Nov 2022 09:57
Full Text Link:
Related URLs: https://www.tan ... 45.2022.2142575 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2023-10
Published Online Date: 2022-11-13
Accepted Date: 2022-11-01
Authors: Worrall, Stephen D. (ORCID Profile 0000-0003-1969-3671)
Wang, Jiawei (ORCID Profile 0000-0001-5690-9107)
Najdanovic-Visak, Vesna (ORCID Profile 0000-0002-1035-0982)



Version: Published Version

License: Creative Commons Attribution

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