Ruofan Gu

COSMO-RS Evaluation and UNIFAC Model Extension for Ionic Liquids and Dimethyl Carbonate/Methanol Systems

Ruofan Gu, Yue Wang, Ke Wang, Guzhong Chen et autres

Dimethyl carbonate (DMC)–methanol (CH 3 OH) separation is an important process in the chemical industries, requiring accurate thermodynamic models for process design and optimization. Although various predictive models, including COSMO-RS and UNIFAC, have been widely applied to analyze ionic liquid (IL)-based extractive …

cn, us (code pays fourni par la source)

Machine Learning‐Aided Rational Screening of Task‐Specific Ionic Liquids

Ruofan Gu, Zhen Song

Ionic liquids (ILs) are renowned for their unique physicochemical properties, flexible structural designability, and expansive chemical diversity. These attributes make ILs highly promising for a wide range of chemical processes, as they can be tailored to meet specific target properties. The fundamental …

cn (code pays fourni par la source)

A large extension of the modified UNIFAC model for IL–solute systems by combining hybrid activity coefficient databases

Ruofan Gu, Jiahui Chen, Jie Cheng, Guzhong Chen et autres

cn, us (code pays fourni par la source)

Graph transformer based transfer learning for aqueous pK prediction of organic small molecules

Yuxin Qiu, Jiahui Chen, Kunchi Xie, Ruofan Gu et autres

cn, pl (code pays fourni par la source)