Predicting CO2 Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms

In this study, new machine-learning-based models have been developed for the prediction of carbon dioxide (CO2) solubility in different Ionic Liquids (ILs). An extensive data set comprising 16,480 experimental data points of CO2 solubility in 296 ILs, co...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Zahra Bastami (21474755) (author)
مؤلفون آخرون:	Mohammad Amin Sobati (7345772) (author), Mahdieh Amereh (21474758) (author)
منشور في:	2025
الموضوعات:	Biochemistry Medicine Plant Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified diverse ionic liquids different ionic liquids swr ), resulting nonlinear methods based demonstrated superior capability modeling complex data 2 </ sup developed using linear 103 different cation lsboost model surpasses lsboost model displayed large data set 2 </ sub nonlinear machine learning dimensional descriptors ), lsboost model rf ), r </ new machine lsboost ). literature demonstrated >< sup training set test set fingerprint descriptors basic descriptors based models anionic descriptors thereby aiding stepwise regression squares boosting relevant variables multilayer perceptron mse values including zero highest accuracy external validation carbon dioxide anion structures 18 categories
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Predicting CO<sub>2</sub> Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms

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