A generative artificial intelligence framework based on a molecular diffusion model for the design of metal-organic frameworks for carbon capture.

Park H, Yan X, Zhu R, Huerta EA, Chaudhuri S, Cooper D, Foster I, Tajkhorshid E

DOI: 10.1038/s42004-023-01090-2
Published: 2024 Feb 14
Container: Communications chemistry
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1038/s42004-023-01090-2,
  title = {A generative artificial intelligence framework based on a molecular diffusion model for the design of metal-organic frameworks for carbon capture.},
  author = {Park H and Yan X and Zhu R and Huerta EA and Chaudhuri S and Cooper D and Foster I and Tajkhorshid E},
  year = {2024},
  journal = {Communications chemistry},
  doi = {10.1038/s42004-023-01090-2},
  url = {https://doi.org/10.1038/s42004-023-01090-2}
}

RIS

TY  - JOUR
TI  - A generative artificial intelligence framework based on a molecular diffusion model for the design of metal-organic frameworks for carbon capture.
AU  - Park H
AU  - Yan X
AU  - Zhu R
AU  - Huerta EA
AU  - Chaudhuri S
AU  - Cooper D
AU  - Foster I
AU  - Tajkhorshid E
PY  - 2024
JO  - Communications chemistry
DO  - 10.1038/s42004-023-01090-2
UR  - https://doi.org/10.1038/s42004-023-01090-2
ER  -

APA

H, P., X, Y., R, Z., EA, H., S, C., D, C., I, F., & E, T. (2024). A generative artificial intelligence framework based on a molecular diffusion model for the design of metal-organic frameworks for carbon capture.. Communications chemistry. https://doi.org/10.1038/s42004-023-01090-2

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pubmed · retrieved 2026-11-10T12:15:24.280Z