Prediction and Interpretability Study of the Glass Transition Temperature of Polyimide Based on Machine Learning with Quantitative Structure–Property Relationship (Tg-QSPR)

发表于 2026-8-5 20:30:04

期刊：The Journal of Physical Chemistry B

文献作者：Tianyong Zhang; Suisui Wang; Yamei Chai; Jianing Yu; Wenxuan Zhu; Liang Li; Bin Li

出版日期：2024-9-12

DOI号：10.1021/acs.jpcb.4c00756

下载链接：https://pubs.acs.org/doi/pdf/10.1021/acs.jpcb.4c00756

文献链接：https://doi.org/10.1021/acs.jpcb.4c00756

当前文献来源于 American Chemical Society (ACS)。

备注信息：

发表于 2026-8-5 20:30:05

: 当前求助已完成，请重新发起求助。
已完结状态的附件将会在24小时内删除。

[ACS] Prediction and Interpretability Study of the Glass Transition Temperature of Polyimide Based on Machine Learning with Quantitative Structure–Property Relationship (Tg-QSPR)

已采纳

同分类求助

最新回复

站点公告

今日热心研友

（热心研友QQ群）

[ACS] Prediction and Interpretability Study of the Glass Transition Temperature of Polyimide Based on Machine Learning with Quantitative Structure–Property Relationship (Tg-QSPR) 一键复制