Machine Learning Guided Assembly of a Nested Gd@Gd @Ni Cluster via Urea Controlled Carbonate Release.

Angew Chem Int Ed Engl

Collaborative Innovation Center of Chemistry for Energy Materials, State Key Laboratory of Physical Chemistry of Solid Surfaces and Department of Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China.

Published: September 2025


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Article 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, [GdNi(MeIDA)(OH)(CO) (HO)]·(ClO)·(HO) (GdNi, HMeIDA = 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@Gd@Ni arrangement, with the innermost Gd 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.

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http://dx.doi.org/10.1002/anie.202516130DOI Listing

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