Machine Learning for Accurate Prediction of Henry’s Law Constant in CO2–Ionic Liquid Systems DOI
Jiaying Wang, Songming Zhu, Jinming Fan

и другие.

ACS Sustainable Chemistry & Engineering, Год журнала: 2025, Номер unknown

Опубликована: Янв. 16, 2025

To accurately and reasonably describe the influence of molecular structure, charge characteristics, other intrinsic properties on Henry's Law Constant (HLC), we have designed Multiscale Group Contribution Descriptor-Machine Learning (MGC-ML) model based revised group contribution method─the weighted contribution. This method extracts first-order descriptors using approach then utilizes a machine learning to impact structure electronic characteristics target properties. Experimental results demonstrate that this not only ensures theoretical reliability but also exhibits exceptionally high predictive accuracy with smaller amount data fewer features. Considering combines chemical principles data-driven approaches, it is likely be proven reasonable effective in addressing more general objectives complex systems.

Язык: Английский

Machine Learning for Accurate Prediction of Henry’s Law Constant in CO2–Ionic Liquid Systems DOI
Jiaying Wang, Songming Zhu, Jinming Fan

и другие.

ACS Sustainable Chemistry & Engineering, Год журнала: 2025, Номер unknown

Опубликована: Янв. 16, 2025

To accurately and reasonably describe the influence of molecular structure, charge characteristics, other intrinsic properties on Henry's Law Constant (HLC), we have designed Multiscale Group Contribution Descriptor-Machine Learning (MGC-ML) model based revised group contribution method─the weighted contribution. This method extracts first-order descriptors using approach then utilizes a machine learning to impact structure electronic characteristics target properties. Experimental results demonstrate that this not only ensures theoretical reliability but also exhibits exceptionally high predictive accuracy with smaller amount data fewer features. Considering combines chemical principles data-driven approaches, it is likely be proven reasonable effective in addressing more general objectives complex systems.

Язык: Английский

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