abstract
The aim of this work was to develop a simple and easy-to-apply model to predict the pH values of deep eutectic solvents (DESs) over a wide range of pH values that can be used in daily work. For this purpose, the pH values of 38 different DESs were measured (ranging from 0.36 to 9.31) and mathematically interpreted. To develop mathematical models, DESs were first numerically described using sigma profiles generated with the COSMOtherm software. After the DESs' description, the following models were used: (i) multiple linear regression (MLR), (ii) piecewise linear regression (PLR), and (iii) artificial neural networks (ANNs) to link the experimental values with the descriptors. Both PLR and ANN were found to be applicable to predict the pH values of DESs with a very high goodness of fit (R-independent validation(2) > 0.8600). Due to the good mathematical correlation of the experimental and predicted values, the sigma profile generated with COSMOtherm could be used as a DES molecular descriptor for the prediction of their pH values.
keywords
DESIGN; GUIDE
subject category
Biochemistry & Molecular Biology; Chemistry
authors
Panic, M; Radovic, M; Bubalo, MC; Radosevic, K; Rogosic, M; Coutinho, JAP; Redovnikovic, IR; Tusek, AJ
our authors
acknowledgements
This work was partly developed within the scope of the project CICECO-Aveiro Institute of Materials, UIDB/50011/2020 & UIDP/50011/2020, financed by national funds through the Portuguese Foundation for Science and Technology/MCTES. This work was also financed by the Croatian science foundation (grant No. 7712).