Metal-organic cages (MOCs) are an emerging class of porous nanocontainers with diverse applications, such as liquid-phase separations¹ and catalysis². However, their solid-state structures and properties remain relatively underexplored, primarily due to the challenges associated with growing and analysing high-quality crystalline MOCs. In this study, we investigate how different MOCs assemble when deposited onto polar surfaces, using AFM to analyse the resulting topologies. This is complemented by an automated workflow for crystal structure prediction (CSP) of MOCs, which enables the rationalization of key structural features in different cage-surface systems. The CSP workflow incorporates high-throughput screening of various crystal lattices using semi-empirical³ methods, machine learning potentials (MACE⁴), and refinement with density functional theory (DFT)⁵. Given the structural diversity of MOCs, this holistic approach is demonstrated using two well-established tetrahedral Fe(II) cages^6,7 with different charges. By integrating experimental and computational methods, we provide both qualitative and quantitative insights into the solid-state structures and properties of MOCs, paving the way for the rational design of systems with novel applications.

 

References:

[1] D. Zhang, T. K. Ronson, Y.-Q. Zou and J. R. Nitschke, Nat. Rev. Chem., 2021, 5, 168–182.

[2] A. B. Grommet, M. Feller and R. Klajn, Nat. Nanotechnol., 2020, 15, 256–271.

[3] S. Spicher and S. Grimme, Angew. Chem., 2020, 132, 15795–15803.

[4] I. Batatia, D. P. Kovács, G. N. C. Simm, C. Ortner, G. Csányi, arXiv, 2022, 2206.07697

[5] J. VandeVondele, M. Krack, F. Mohamed, M. Parrinello, T. Chassaing and J. Hutter, Comput. Phys. Commun., 2005, 167, 103–128.

[6] P. Mal, D. Schultz, K. Beyeh, K. Rissanen and J. Nitschke, Angew. Chem. Int. Ed., 2008, 47, 8297–8301.

[7] R. A. Bilbeisi , J. K. Clegg , N. Elgrishi , X. de Hatten , M. Devillard , B. Breiner , P. Mal and J. R. Nitschke , J. Am. Chem. Soc., 2012, 134 , 5110–5119.