Exploring the chemical space of ionic liquids for CO2 dissolution through generative machine learning models

Exploring the chemical space of ionic liquids for CO2 dissolution through generative machine learning models

For discovering uncharted chemical space of ionic liquids (ILs) for CO2 dissolution, a reliable generative framework combining re-balanced variational autoencoder (VAE), artificial neural network (ANN), and particle swarm optimization (PSO) is developed based on a comprehensive experimental solubili...

Full description

Saved in:
Bibliographic Details
Main Authors: Xiuxian Chen, Guzhong Chen, Kunchi Xie, Jie Cheng, Jiahui Chen, Zhen Song, Zhiwen Qi
Format: Article
Language:English
Published: KeAi Communications Co. Ltd. 2025-09-01
Series:Green Chemical Engineering
Subjects:
Ionic liquids
CO2 solubility
Variational autoencoder
Particle swarm optimization
Chemical space exploration
Online Access:http://www.sciencedirect.com/science/article/pii/S2666952824000414
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://www.sciencedirect.com/science/article/pii/S2666952824000414

Similar Items