文献类型：期刊文献

英文题名：Data-Driven Prediction of Flory-Huggins Parameter for Quantifying Polymer-Solvent Interaction

作者：Zhu, Jiayi[1];Lin, Li-Hong[2];Niu, Haoren[3];Shang, Qiaoyan[1];Wang, Qiang[3];Yan, Fangyou[3];Li, Jin-Jin[4]

机构：[1]Tianjin Univ Sci & Technol, Sch Marine & Environm Sci, Tianjin 300457, Peoples R China;[2]East China Univ Sci & Technol, Sch Chem & Mol Engn, Shanghai 200237, Peoples R China;[3]Tianjin Univ Sci & Technol, Sch Mat Sci & Chem Engn, Tianjin 300457, Peoples R China;[4]East China Univ Sci & Technol, Sch Chem Engn, State Key Lab Chem Engn, Shanghai 200237, Peoples R China

年份：2025

卷号：64

期号：15

起止页码：7862

外文期刊名：INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

收录：;EI(收录号：20251518191856);WOS:【SCI-EXPANDED(收录号:WOS:001460230000001)】；

基金：This work was financially supported by the National Natural Science Foundation of China (22278319, 22378116, and 22106094) and Shanghai Rising-Star Program (22QA1402800).

语种：英文

摘要：The Flory-Huggins interaction parameter is an influential thermodynamic parameter for quantifying polymer-solvent interaction. The data-driven quantitative structure-property relationship (QSPR) model provides a rapid and accurate route to obtain the Flory-Huggins parameter of polymer-solvent mixtures. To evaluate the correlation between the polymer-solvent structure and the Flory-Huggins parameter, we developed a QSPR model based on 29 norm descriptors. To overcome the diversity of structural representations of a polymer, a ring repeating unit is adopted for unique structural representation of the polymers. Considering the effects of polymers, solvents, and polymer-solvent interactions on the Flory-Huggins parameters, the descriptors are divided into three parts. The results of statistical parameter analysis indicate that the QSPR model exhibits good prediction performance (R 2 test = 0.9348, AAEtest = 0.1943) and robustness (Q 2 LOO-CV = 0.9177). This work offers a quantitative reference and a tool to understand polymer-solvent interactions.