Metal-organic frameworks (MOFs) are crystalline materials consisting of a metal node and an organic linker.¹ By combining different metal nodes and organic linkers, chemists can synthesize infinite materials² for applications ranging from gas separation, gas storage, sensing, catalysis, etc. This makes MOFs the ideal playground for data science. In this presentation we show how data science can support help designing MOFs for carbon capture applications. In  particular, we show how data-science methods^3,4 can be used to obtain insights into questions for which conventional theory does not have an answer, such as the oxidation state of the metal⁵ and the heat capacity of a MOF.⁶ In addition, we show how data science can help us identifying the characteristics of the top-performing materials for a carbon capture process. ⁷

References

¹                  H. Furukawa, K. E. Cordova, M. O'Keeffe, and O. M. Yaghi, The Chemistry and Applications of Metal-Organic Frameworks Science 341 (6149), 974 (2013) http://dx.doi.org/10.1126/Science.1230444

²                  S. Lee, B. Kim, H. Cho, H. Lee, S. Y. Lee, E. S. Cho, and J. Kim, Computational Screening of Trillions of Metal-Organic Frameworks for High-Performance Methane Storage Acs Appl Mater Inter 13 (20), 23647 (2021) http://dx.doi.org/10.1021/acsami.1c02471

³                  K. M. Jablonka, D. Ongari, S. M. Moosavi, and B. Smit, Big-Data Science in Porous Materials: Materials Genomics and Machine Learning Chem. Rev. 120 (16), 8066 (2020) http://dx.doi.org/10.1021/acs.chemrev.0c00004

⁴                  S. M. Moosavi, K. M. Jablonka, and B. Smit, The Role of Machine Learning in the Understanding and Design of Materials J. Am. Chem. Soc. 142 (48), 20273 (2020) http://dx.doi.org/10.1021/jacs.0c09105

⁵                  K. M. Jablonka, D. Ongari, S. M. Moosavi, and B. Smit, Using collective knowledge to assign oxidation states of metal cations in metal-organic frameworks Nat. Chem. 13, 771 (2021) http://dx.doi.org/10.1038/s41557-021-00717-y

⁶                  S. M. Moosavi, B. Á. Novotny, D. Ongari, E. Moubarak, M. Asgari, Ö. Kadioglu, C. Charalambous, A. Ortega-Guerrero, A. H. Farmahini, L. Sarkisov, S. Garcia, F. Noé, and B. Smit, A data-science approach to predict the heat capacity of nanoporous materials Nat Mater 21, 1419 (2022) http://dx.doi.org/10.1038/s41563-022-01374-3

⁷                  C. Charalambous, E. Moubarak, J. Schilling, E. Sanchez Fernandez, J.-Y. Wang, L. Herraiz, F. Mcilwaine, K. M. Jablonka, S. M. Moosavi, J. Van Herck, G. Mouchaham, C. Serre, A. Bardow, B. Smit, and S. Garcia, Shedding Light on the Stakeholders' Perspectives for Carbon Capture. ChemRxiv  (2023) http://dx.doi.org/10.26434/chemrxiv-2023-sn90q