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MoDoop: An Automated Computational Approach for COSMO-RS Prediction of Biopolymer Solubilities in Ionic Liquids

Chu, Yunhan; He, Xuezhong
Journal article, Peer reviewed
Published version
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URI
http://hdl.handle.net/11250/2592934
Date
2019
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  • Institutt for kjemisk prosessteknologi [1875]
  • Publikasjoner fra CRIStin - NTNU [41869]
Original version
ACS Omega. 2019, 4 2337-2343.   10.1021/acsomega.8b03255
Abstract
An automated computational framework (MoDoop) was developed to predict the biopolymer solubilities in ionic liquids (ILs) on the basis of conductor-like screening model for real solvents calculations of two thermodynamic properties: logarithmic activity coefficient (ln γ) at infinite dilution and excess enthalpy (HE) of mixture. The calculation was based on the optimized two-dimensional structures of biopolymer models and ILs by searching the lowest-energy conformer and optimizing molecular geometry. Three lignin models together with one IL dataset were used to evaluate the prediction ability of the developed method. The evaluation results show that ln γ is a more reliable property to predict lignin solubilities in ILs and the p-coumaryl alcohol model is considered as the best model to represent lignin molecules. The developed MoDoop approach is efficient for rapid in silico screening of suitable ionic liquids to dissolve biopolymers.
Publisher
American Chemical Society
Journal
ACS Omega

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