Machine Learning Guided Assembly of a Nested Gd<sub>20</sub>@Gd<sub>32</sub> @Ni<sub>36</sub> Cluster via Urea Controlled Carbonate Release
Ming‐Qiang Qi, Ruiwu Yang, Jianyu Wu, Jianan Chen, Yulin Qi, Xin‐Ya Diao, Ming‐Hao Du, Yibin Jiang, Cheng Wang, La‐Sheng Long, Lan‐Sun Zheng, Xiang‐Jian Kong
Abstract
Abstract Lanthanide‐based polyhedral clusters are of great interest due to their unique geometries and functional properties, but their controlled synthesis remains a major challenge. Here, we report a nested three‐shell cluster, [Gd 52 Ni 36 (MeIDA) 36 (OH) 114 (CO 3 ) 12 (H 2 O) 48 ]·(ClO 4 ) 18 ·(H 2 O) 21 ( Gd 52 Ni 36 , H 2 MeIDA = N ‐Methyliminodiacetic acid), achieved by using urea as a slow‐release carbonate source to direct the formation of a dodecahedral inner shell. Single‐crystal X‐ray diffraction reveals a unique Gd 20 @Gd 32 @Ni 36 arrangement, with the innermost Gd 20 forming a Platonic dodecahedron templated by carbonate. A machine learning–guided, high‐throughput synthesis platform enabled the exploration of 780 reaction conditions, uncovering key parameters and phase boundaries governing cluster formation. This work demonstrates data‐driven strategies can accelerate the discovery of complex lanthanide architectures.