Prediction of ionic liquid thermophysical properties by group contribution method using random forest regression

Prediction of ionic liquid thermophysical properties by group contribution method using random forest regression

Ionic liquids are tunable, there are vast combinations of cations and anions and attached substituent groups that can be combined together to achieve a target property. Mathematical equations in which the contributions of each component groups of an ionic liquid are considered in a predictive model...

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Bibliographic Details
Main Author: Nuqui, Jesus Patrick E.
Format: text
Language:English
Published: Animo Repository 2023
Subjects:
Materials—Thermal properties
Materials—Thermal conductivity
Chemical Engineering
Engineering
Thermodynamics
Online Access:https://animorepository.dlsu.edu.ph/etdm_chemeng/20
https://animorepository.dlsu.edu.ph/context/etdm_chemeng/article/1020/viewcontent/Prediction_of_ionic_liquid_thermophysical_properties_by_group_contribution_method_using_random_forest_regression.pdf
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Institution: De La Salle University
Language: English

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https://animorepository.dlsu.edu.ph/etdm_chemeng/20
https://animorepository.dlsu.edu.ph/context/etdm_chemeng/article/1020/viewcontent/Prediction_of_ionic_liquid_thermophysical_properties_by_group_contribution_method_using_random_forest_regression.pdf

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