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Synthesis of pillar-layered metal–organic frameworks with variable backbones through sequence control

Nature Chemistry volume 17, pages 421–428 (2025)Cite this article

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Abstract

The properties and functions of metal–organic frameworks (MOFs) can be tailored by tuning their structure, including their shape, porosity and topology. However, the design and synthesis of complex structures in a predictable manner remains challenging. Here we report the preparation of a series of isomeric pillar-layered MOFs, and we show that their three-dimensional topology can be controlled by altering the layer stacking. This enables variability on the backbone structure, as well as diverse spatial arrangements of pillars and the partitioning of pore space into several kinds of cages packing in distinct sequences. These sequence-controlled MOFs (SC-MOF-1–6) showcase ultrahigh benzene capture capacities at low-pressure and high volumetric and gravimetric uptake performances in high-pressure methane storage. We provide the construction principles of the SC-MOFs and predict nearly 2,000 possible SC-networks with sophisticated composition sequences at the atomic level by using a Python script.

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Fig. 1: Sequence-controlled materials.
Fig. 2: Schematic representation of topology-guided synthesis of pillar-layered SC-MOF-1.
Fig. 3: Layer and pillar sequences in SC-MOF-2–6.
Fig. 4: Representation of cage sequences in SC-MOF-1–6 viewed from a axis.
Fig. 5: The layer, pillar and cage sequences in the predicted SC-MOFs.
Fig. 6: Ar, CH4 and benzene adsorption studies for SC-MOF-1–4.

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Data availability

All crystallographic data have been deposited with the Cambridge Crystallographic Data Centre, with reference numbers 2236913 (SC-MOF-1), 2236914 (SC-MOF-2), 2236915 (SC-MOF-3), 2236916 (SC-MOF-4), 2236917 (SC-MOF-5) and 2387166 (SC-MOF-6). Copies of the data can be obtained free of charge via https://www.ccdc.cam.ac.uk/structures/. All other data are included in the Supplementary Information. Source data are available via figshare at https://doi.org/10.6084/m9.figshare.27828132 (ref. 54). Source data are provided with this paper.

Code availability

The Python script is available via figshare at https://doi.org/10.6084/m9.figshare.27828132 (ref. 54).

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Acknowledgements

We thank the Analysis and Testing Center at Central China Normal University, Wuhan, China, for research support. We thank Q. Li for discussions in the stage of the paper preparation. This work was supported by the National Natural Science Foundation of China (grant numbers 22101093, B.T., 22125304 and 22032005, A.Z.), the Natural Science Foundation of Hubei Province, China (grant number 2022CFB163, B.T.), the Knowledge Innovation Program of Wuhan-Shuguang Project (B.T.) and the Fundamental Research Funds for the Central Universities (grant numbers CCNU22QN008 and CCNU24JCPT017, B.T.). We also acknowledge the computational resources provided by High-Performance Computing Center of Wuhan University of Science and Technology.

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Authors and Affiliations

  1. Engineering Research Center of Photoenergy Utilization for Pollution Control and Carbon Reduction, Ministry of Education, State Key Laboratory of Green Pesticide, College of Chemistry, Central China Normal University, Wuhan, China

    Jingjing Yuan, Ming Yang, Bin Yang, Shuting Chen & Binbin Tu

  2. Interdisciplinary Institute of NMR and Molecular Sciences, School of Chemistry and Chemical Engineering, The State Key Laboratory of Refractories and Metallurgy, Wuhan University of Science and Technology, Wuhan, China

    Zhiqiang Liu, Mingyu Wan & Anmin Zheng

  3. Key Laboratory of Hubei Province for Coal Conversion and New Carbon Materials, School of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, Wuhan, China

    Qingqing Pang

  4. Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan, China

    Anmin Zheng

  5. Wuhan Institute of Photochemistry and Technology, Wuhan, China

    Binbin Tu

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Contributions

B.T. conceived the idea. J.Y., Q.P. and B.T. developed the concept, supervised the project and wrote the paper. J.Y. and M.Y. synthesized the compounds and performed the material characterizations. J.Y. and S.C. collected and analysed the gas/vapour adsorption data. B.Y. performed the GCMC simulations. Z.L., M.W. and A.Z. calculated the thermodynamic energies of the frameworks. J.Y., Q.P. and B.T. performed the structural analyses and new structure prediction.

Corresponding authors

Correspondence to Qingqing Pang, Mingyu Wan, Anmin Zheng or Binbin Tu.

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Competing interests

The authors declare no competing interests.

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Peer review information

Nature Chemistry thanks Volodymyr Bon, Daqiang Yuan and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–190, Discussion and Tables 1–63.

Supplementary Data 1

Crystallographic information files for SC-MOF-1 (CCDC 2236913).

Supplementary Data 2

Crystallographic information files for SC-MOF-2 (CCDC 2236914).

Supplementary Data 3

Crystallographic information files for SC-MOF-3 (CCDC 2236915).

Supplementary Data 4

Crystallographic information files for SC-MOF-4 (CCDC 2236916).

Supplementary Data 5

Crystallographic information files for SC-MOF-5 (CCDC 2236917).

Supplementary Data 6

Crystallographic information files for SC-MOF-6 (CCDC 2387166).

Supplementary Data 7

Python code file for layer sequences calculation.

Supplementary Data 8

Layer sequences for the cases with 2–18 layers in the MRU.

Source data

Source Data Fig. 6

Statistical source data for Fig. 6.

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Yuan, J., Yang, M., Yang, B. et al. Synthesis of pillar-layered metal–organic frameworks with variable backbones through sequence control. Nat. Chem. 17, 421–428 (2025). https://doi.org/10.1038/s41557-024-01717-4

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