Prediction of the melting points of ionic liquids using machine learning approach.
مؤلف
Al-Busaidiyah, Suhaila Salim Hamed.
الملخص الإنجليزي
Ionic liquids (ILs) have been receiving special attention since the mid-1990 owing to their unique
physiochemical characteristics. Ionic liquids are currently used as a green solvents intended to
replace conventional volatile solvents and hold a significant promise for applications in energy
storage. This thesis contributes to the chemical engineering industry by undertaking a
comprehensive study, aiming to develop a model capable for predicting the melting point of the
ILs using Group Method of Data Handling (GMDH). The developed model resulted with 𝑅
2 value
of 0.78 with an approximate root mean square error (RMSE) of 36 K, providing valuable insights
and predictive capabilities for the chemical engineering industry.
