TY - JOUR
T1 - Quantitative structure properties relationship for deep eutectic solvents using Sσ-profile as molecular descriptors
AU - Lemaoui, Tarek
AU - Hammoudi, Nour El Houda
AU - Alnashef, Inas M.
AU - Balsamo, Marco
AU - Erto, Alessandro
AU - Ernst, Barbara
AU - Benguerba, Yacine
N1 - Funding Information:
This work was supported by Université Ferhat ABBAS Sétif-1, Algeria, and partially funded by Khalifa University , UAE, through grant CIRA-2018-69 .
Funding Information:
This work was supported by Universit? Ferhat ABBAS S?tif-1, Algeria, and partially funded by Khalifa University, UAE, through grant CIRA-2018-69.
Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - Computer assisted Quantitative Structure Property Relationship (QSPRs) has proven to be an accurate, reliable and cost-effective method for predicting the physicochemical properties of DESs, via a set of molecular descriptors. In this work, experimental data on the properties of DESs at different temperatures were taken from different bibliographic sources. The Conductor like Screen Model for Real Solutions (COSMO-RS) was used to predict the thermodynamic properties of DESs. A modeling analysis was conducted in order to provide a model for the prediction of specific DESs properties, such as viscosity density, etc. The used methodology allowed achieving reliable results as all the models showed high regression performances. The corresponding model parameters were determined and an analysis of variance allowed identification of the most significant factors of the retrieved models. Finally, an independent set of experimental data relevant to the modelled physical properties of DESs was used to test the obtained models. In most cases, there was a good agreement between the experimental and predicted values of the investigated properties.
AB - Computer assisted Quantitative Structure Property Relationship (QSPRs) has proven to be an accurate, reliable and cost-effective method for predicting the physicochemical properties of DESs, via a set of molecular descriptors. In this work, experimental data on the properties of DESs at different temperatures were taken from different bibliographic sources. The Conductor like Screen Model for Real Solutions (COSMO-RS) was used to predict the thermodynamic properties of DESs. A modeling analysis was conducted in order to provide a model for the prediction of specific DESs properties, such as viscosity density, etc. The used methodology allowed achieving reliable results as all the models showed high regression performances. The corresponding model parameters were determined and an analysis of variance allowed identification of the most significant factors of the retrieved models. Finally, an independent set of experimental data relevant to the modelled physical properties of DESs was used to test the obtained models. In most cases, there was a good agreement between the experimental and predicted values of the investigated properties.
KW - COSMO-RS
KW - Deep eutectic solvents
KW - Modeling
KW - Multilinear regression
KW - Physiochemical properties
KW - Quantitative Structure Property Relationship (QSPR)
UR - http://www.scopus.com/inward/record.url?scp=85083900142&partnerID=8YFLogxK
U2 - 10.1016/j.molliq.2020.113165
DO - 10.1016/j.molliq.2020.113165
M3 - Article
AN - SCOPUS:85083900142
SN - 0167-7322
VL - 309
JO - Journal of Molecular Liquids
JF - Journal of Molecular Liquids
M1 - 113165
ER -