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High-throughput transition-state searches in zeolite nanopores

Nature Computational Science (2026) Cite this article

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Abstract

Zeolites are essential catalysts for organic transformations owing to their confined nanoporous environments. However, experimental mechanistic studies are costly, and traditional simulations lack scalability, relying on manual structural manipulation. Here we introduce pore transition-state finder (PoTS), an automated pipeline for locating transition states (TS) in zeolites. PoTS identifies gas-phase TSs via density functional theory, docks them near active sites in zeolite pores and uses their reaction modes to seed condensed-phase TS searches with the dimer method. This automation reduces user intervention, improves success rates and bypasses the need for long path-following calculations. We apply PoTS to a density functional theory-level dataset of zeolite-confined TSs, finding good experimental agreement in both cases. Last, we propose a path to address the limitations we observe regarding unsuccessful TS searches and insufficient theory in other reactions, such as alkene cracking.

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Fig. 1: Overview of the PoTS workflow, zeolites studied and reactions.
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Fig. 2: DEB transalkylation mechanisms and isomeric species.
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Fig. 3: Calculated free energy profiles for DEB translakylation.
The alternative text for this image may have been generated using AI.
Fig. 4: Heat map of rate-determining barriers across zeolites.
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Fig. 5: RC mechanisms and TS examples; cracking scheme.
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Data availability

The source data for Figs. 3 and 4 are available via Zenodo at https://doi.org/10.5281/zenodo.15200092 (ref. 68).

Code availability

The computational code base described in the Methods for building zeolite models and running TS searches with the dimer method on VASP reported in the work is available free of charge under the MIT license at the Learning Matter group code repositories VOID60 and PoTS61.

Change history

  • 12 March 2026

    In the version of the article initially published, refs. 60 and 61 were swapped and have now been corrected so that ref. 60 is “Schwalbe-Koda, D. learningmatter-mit/VOID 1.0.1. Zenodo https://doi.org/10.5281/zenodo.5260054 (2021)” and ref. 61 is “Ferri-Vicedo, P. learningmatter-mit/POTS. Zenodo https://doi.org/10.5281/zenodo.17901717 (2025)” in the HTML and PDF versions of the article.

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Acknowledgements

We acknowledge the MIT SuperCloud and Lincoln Laboratory Supercomputing Center for providing high-performance computing (HPC) resources that have contributed to the research results reported within this Article. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy Office of Science User Facility using NERSC awards grant nos. BES-ERCAP-m4604 and BES-ERCAP-m4866. P.F.-V. thanks Fundacion Ramon Areces for his postdoctoral fellowship. A.S. also acknowledges support from the National Defense Science and Engineering Graduate Fellowship. We thank M. Xie (MIT) for helpful discussions and suggestions. P.F.-V., A.H. and R.G.-B. acknowledge financial support from Deshpande Center and ExxonMobil Technology and Engineering Company.

Author information

Authors and Affiliations

  1. Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Pau Ferri-Vicedo, Alexander J. Hoffman, Avni Singhal & Rafael Gómez-Bombarelli

Authors
  1. Pau Ferri-Vicedo
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  2. Alexander J. Hoffman
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  3. Avni Singhal
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  4. Rafael Gómez-Bombarelli
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Contributions

P.F.-V. designed and implemented the PoTS pipeline, ran DFT calculations and analyzed results. A.J.H. assisted with PoTS pipeline design and provided guidance for solid-state calculations. A.S. assisted with the PoTS pipeline designed and provided guidance with DFT gas phase calculations. R.G.-B. conceived the project, supervised the research and contributed to securing funding. All authors contributed to results discussion and paper writing.

Corresponding author

Correspondence to Rafael Gómez-Bombarelli.

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The authors declare no competing interests.

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Nature Computational Science thanks the anonymous reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Kaitlin McCardle, in collaboration with the Nature Computational Science team. Peer reviewer reports are available.

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Supplementary information

Supplementary Information (download PDF )

Supplementary Figs. 1–65 and Tables 1–16.

Peer Review File (download PDF )

Supplementary Data Table 1 (download XLSX )

Zeolite multistep path relative free energies in kJ mol−1. Global MEPs starred at Fig. 3 in the main Article are highlighted in green color.

Supplementary Data Table 2 (download XLSX )

Zeolite multistep path free energy barriers in kJ mol−1. Global MEPs starred at Fig. 4 in the main Article are highlighted in green color.

Supplementary Data Table 3 (download XLSX )

Zeolite direct path relative free energies in kJ mol−1. Free energy barriers reported on the main manuscript correspond to the TS1 energy value. Global MEPs starred at Fig. 5 in the main Article are highlighted in green color.

Supplementary Data Table 4 (download XLSX )

Free pore area (Ų) available in each zeolite channel after accommodating each TS structure. The free pore area is calculated as: channel area = π × ((max D Sphere IZA)/2)2, TS area = π × (middle axis/2) × (minimum axis)/2, free pore area = channel area – TS area. A visual representation of these calculations is provided in Supplementary Fig. 39, and the corresponding data are illustrated in Supplementary Fig. 40. Max D sphere values used according to IZA database website, IWV = 8.05 Å, IWV = 8.54 Å, UTL = 9.3 Å, FAU = 11.24 Å.

Supplementary Data Table 5 (download XLSX )

Framework, isomer combination, T site, TS label, mean minimum distance and mean maximum distance in Amstrongs (Å).

Supplementary Data Table 6 (download XLSX )

Transalkylation paths have been rescaled relative to the minimum I0 energy identified among the BOG (T1: meta-benzene), IWV (T7: ortho-benzene) and UTL (T2: para-benzene). Scaled disproportionation pathways have been referenced to the minimum I0 energy found among BOG (T1: meta–para), IWV (T7: meta–para) and UTL (T2: para–para).

Supplementary Data Table 7 (download XLSX )

Scaled disproportionation pathways have been referenced to the minimum I0 energy found among BOG (T1: meta–para), IWV (T7: meta–para), and UTL (T2: para–para).

Supplementary Data Table 8 (download XLSX )

Relative free energy stabilities, GTA − GTB, for the different BOG, IWV and UTL models studied in kJ mol−1. Intermediates from I column, TSs from TS column.

Extended Data IRC.CIF (download TXT )

An extended data file containing the CIF with the converged structures of the optimized reactant, IRC reactant-side minimum, optimized product and IRC product-side minimum is provided, enabling direct verification of all structural assignments.

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Ferri-Vicedo, P., Hoffman, A.J., Singhal, A. et al. High-throughput transition-state searches in zeolite nanopores. Nat Comput Sci (2026). https://doi.org/10.1038/s43588-026-00964-4

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