Insights into the estimation of surface tensions of mixtures based on designable green materials using an ensemble learning scheme.

ABSTRACT: Precise estimation of the physical properties of both ionic liquids (ILs) and their mixtures is crucial for engineers to successfully design new industrial processes. Among these properties, surface tension is especially important. It's not only necessary to have knowledge of the properties of pure ILs, but also of their mixtures to ensure optimal utilization in a variety of applications. In this regard, this study aimed to evaluate the effectiveness of Stochastic Gradient Boosting (SGB) tree in modeling surface tensions of binary mixtures of various ionic liquids (ILs) using a comprehensive dataset. The dataset comprised 4010 experimental data points from 48 different ILs and 20 non-IL components, covering a surface tension range of 0.0157-0.0727 N m^-1 across a temperature rang

SUBMITTER: Soleimani R 

PROVIDER: S-EPMC10465615 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature