MLR Data-Driven for the Prediction of Infinite Dilution Activity Coefficient of Water in Ionic Liquids (ILs) Using QSPR-Based COSMO Descriptors.

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Tác giả: Ville Alopaeus, Ali Ebrahimpoor Gorji, Juho-Pekka Laakso, Petri Uusi-Kyyny

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: United States : Journal of chemical information and modeling , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 250369

To predict the partial molar excess enthalpy, entropy at infinite dilution, and phase equilibria, the availability of an infinite dilution activity coefficient is vital. The "quantitative structure-activity/property relationship" (QSAR/QSPR) approach has been used for the prediction of infinite dilution activity coefficient of water in ionic liquids using an extensive data set. The data set comprised 380 data points including 68 unique ILs at a wide range of temperatures, which is more extensive than previously published data sets. Moreover, new predictive QSAR/QSPR models including novel molecular descriptors, called "COSMO-RS descriptors", have been developed. Using two different techniques of external validation, the data set was divided to the training set for the development of models and to the validation set for external validation. Unlike former available models, internal validation using leave one/multi out-cross validations (LOO-CV/LMO-CV) and Y-scrambling methods were performed on the models using statistical parameters for further assessment. According to the obtained results of statistical parameters (
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