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MoDoop: An Automated Computational Approach for COSMO-RS Prediction of Biopolymer Solubilities in Ionic Liquids
[Image: see text] 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 infini...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6648271/ https://www.ncbi.nlm.nih.gov/pubmed/31459475 http://dx.doi.org/10.1021/acsomega.8b03255 |
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author | Chu, Yunhan He, Xuezhong |
author_facet | Chu, Yunhan He, Xuezhong |
author_sort | Chu, Yunhan |
collection | PubMed |
description | [Image: see text] 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 (H(E)) 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. |
format | Online Article Text |
id | pubmed-6648271 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-66482712019-08-27 MoDoop: An Automated Computational Approach for COSMO-RS Prediction of Biopolymer Solubilities in Ionic Liquids Chu, Yunhan He, Xuezhong ACS Omega [Image: see text] 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 (H(E)) 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. American Chemical Society 2019-01-30 /pmc/articles/PMC6648271/ /pubmed/31459475 http://dx.doi.org/10.1021/acsomega.8b03255 Text en Copyright © 2019 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Chu, Yunhan He, Xuezhong MoDoop: An Automated Computational Approach for COSMO-RS Prediction of Biopolymer Solubilities in Ionic Liquids |
title | MoDoop: An Automated Computational Approach for COSMO-RS
Prediction of Biopolymer Solubilities in Ionic Liquids |
title_full | MoDoop: An Automated Computational Approach for COSMO-RS
Prediction of Biopolymer Solubilities in Ionic Liquids |
title_fullStr | MoDoop: An Automated Computational Approach for COSMO-RS
Prediction of Biopolymer Solubilities in Ionic Liquids |
title_full_unstemmed | MoDoop: An Automated Computational Approach for COSMO-RS
Prediction of Biopolymer Solubilities in Ionic Liquids |
title_short | MoDoop: An Automated Computational Approach for COSMO-RS
Prediction of Biopolymer Solubilities in Ionic Liquids |
title_sort | modoop: an automated computational approach for cosmo-rs
prediction of biopolymer solubilities in ionic liquids |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6648271/ https://www.ncbi.nlm.nih.gov/pubmed/31459475 http://dx.doi.org/10.1021/acsomega.8b03255 |
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