Data-driven efficient synthetic exploration of anionic lanthanide-based metal-organic frameworks
Data-driven efficient synthetic exploration of anionic lanthanide-based metal-organic frameworks
复制标题
数据驱动的阴离子镧系金属有机框架的高效合成探索
DOI：
10.1039/d2cc04985f
复制
发表时间：
2022
影响因子：
4.9
通讯作者：
Tanaka Daisuke
中科院分区：
文献类型：
--
作者：
Kitamura Yu;Nakamura Yuiga;Sugimoto Kunihisa;Yoshikawa Hirofumi;Tanaka Daisuke
采用数据驱动的方法研究了用对苯二甲酸盐合成镧系金属有机骨架（Ln-BDC-MOFs）。视觉映射先前报道的合成条件表明存在未探索的新型ln - bdc - mof的搜索空间。通过关注未开发的化学反应空间，我们成功地合成了一系列新的阴离子ln - bdc - mof， KGF-15，它具有作为Cu2+离子发光传感器的潜力。这种综合探索方法可以显著减少发现新材料所需的实验努力。
The synthesis of lanthanide metal–organic frameworks with terephthalate (Ln-BDC-MOFs) was investigated using a data-driven approach. Visually mapping the previously reported synthetic conditions suggested the existence of unexplored search spaces for novel Ln-BDC-MOFs. By focusing on the unexplored chemical reaction space, we successfully synthesized a series of new anionic Ln-BDC-MOFs, KGF-15, which demonstrated potential as luminescent sensors for Cu2+ ions. This synthetic exploration approach can significantly reduce the experimental effort required to discover new materials.