A GPT-4 Reticular Chemist for Guiding MOF Discovery.
Artificial Intelligence
Crystals
Large Language Model
Metal-Organic Frameworks
Synthesis
Journal
Angewandte Chemie (International ed. in English)
ISSN: 1521-3773
Titre abrégé: Angew Chem Int Ed Engl
Pays: Germany
ID NLM: 0370543
Informations de publication
Date de publication:
13 Nov 2023
13 Nov 2023
Historique:
received:
16
08
2023
medline:
6
10
2023
pubmed:
6
10
2023
entrez:
5
10
2023
Statut:
ppublish
Résumé
We present a new framework integrating the AI model GPT-4 into the iterative process of reticular chemistry experimentation, leveraging a cooperative workflow of interaction between AI and a human researcher. This GPT-4 Reticular Chemist is an integrated system composed of three phases. Each of these utilizes GPT-4 in various capacities, wherein GPT-4 provides detailed instructions for chemical experimentation and the human provides feedback on the experimental outcomes, including both success and failures, for the in-context learning of AI in the next iteration. This iterative human-AI interaction enabled GPT-4 to learn from the outcomes, much like an experienced chemist, by a prompt-learning strategy. Importantly, the system is based on natural language for both development and operation, eliminating the need for coding skills, and thus, make it accessible to all chemists. Our collaboration with GPT-4 Reticular Chemist guided the discovery of an isoreticular series of MOFs, with each synthesis fine-tuned through iterative feedback and expert suggestions. This workflow presents a potential for broader applications in scientific research by harnessing the capability of large language models like GPT-4 to enhance the feasibility and efficiency of research activities.
Identifiants
pubmed: 37798813
doi: 10.1002/anie.202311983
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e202311983Subventions
Organisme : Defense Advanced Research Projects Agency
ID : HR0011-21-C-0020
Organisme : Kavli Foundation
ID : Kavli ENSI Graduate Student Fellowship
Organisme : BIDMaP
Informations de copyright
© 2023 Wiley-VCH GmbH.
Références
O. M. Yaghi, M. J. Kalmutzki, C. S. Diercks, Introduction to reticular chemistry: metal-organic frameworks and covalent organic frameworks, John Wiley & Sons, Hoboken, 2019;
O. M. Yaghi, M. O′Keeffe, N. W. Ockwig, H. K. Chae, M. Eddaoudi, J. Kim, Nature 2003, 423, 705-714;
R. Freund, S. Canossa, S. M. Cohen, W. Yan, H. Deng, V. Guillerm, M. Eddaoudi, D. G. Madden, D. Fairen-Jimenez, H. Lyu, Angew. Chem. Int. Ed. 2021, 60, 23946-23974.
C. Gropp, S. Canossa, S. Wuttke, F. Gándara, Q. Li, L. Gagliardi, O. M. Yaghi, ACS Cent. Sci. 2020, 6, 1255.
OpenAI, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2303.08774;
S. Bubeck, V. Chandrasekaran, R. Eldan, J. Gehrke, E. Horvitz, E. Kamar, P. Lee, Y. T. Lee, Y. Li, S. Lundberg, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2303.12712;
T. Hope, D. Downey, D. S. Weld, O. Etzioni, E. Horvitz, Commun. ACM 2023, 66, 62-73;
H. Wang, T. Fu, Y. Du, W. Gao, K. Huang, Z. Liu, P. Chandak, S. Liu, P. Van Katwyk, A. Deac, Nature 2023, 620, 47-60;
Y. Liu, T. Han, S. Ma, J. Zhang, Y. Yang, J. Tian, H. He, A. Li, M. He, Z. Liu, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2304.01852;
A. D. White, Nat. Chem. Rev. 2023, 7, 457-458.
H. Lyu, Z. Ji, S. Wuttke, O. M. Yaghi, Chem 2020, 6, 2219-2241.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, I. Polosukhin, NIPS 2017, 30;
C. M. Castro Nascimento, A. S. Pimentel, J. Chem. Inf. Model. 2023, 63, 1649-1655;
A. M. Bran, S. Cox, A. D. White, P. Schwaller, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2304.05376.
Z. Yang, Y. Wang, L. Zhang, bioRxiv preprint 2023, https://doi.org/10.1101/2023.04.19.537579;
M. M. Rahman, H. J. Terano, M. N. Rahman, A. Salamzadeh, M. S. Rahaman, J. Educ. Manage. Studies 2023, 3, https://doi.org/10.52631/jemds.v3i1.175.
Z. Zheng, O. Zhang, C. Borgs, J. T. Chayes, O. M. Yaghi, J. Am. Chem. Soc. 2023, 145, 18048-18062;
S. Wang, H. Scells, B. Koopman, G. Zuccon, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2302.03495.
T. M. Clark, J. Chem. Educ. 2023, 100, 1905-1916;
K. Hatakeyama-Sato, N. Yamane, Y. Igarashi, Y. Nabae, T. Hayakawa, ChemRxiv preprint 2023, https://doi.org/10.26434/chemrxiv-2023-s1x5p;
S. Fergus, M. Botha, M. Ostovar, J. Chem. Educ. 2023, 100, 1672-1675;
R. P. d. Santos, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2305.11890;
J.-P. Vert, Nat. Biotechnol. 2023, 41, 750-751.
Y. Kang, J. Kim, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2308.01423;
D. Noever, F. McKee, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2301.13382.
A. G. Parameswaran, S. Shankar, P. Asawa, N. Jain, Y. Wang, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2308.03854;
Y. Zhou, A. I. Muresanu, Z. Han, K. Paster, S. Pitis, H. Chan, J. Ba, arXiv preprint 2022, https://doi.org/10.48550/arXiv.2211.01910;
J. White, Q. Fu, S. Hays, M. Sandborn, C. Olea, H. Gilbert, A. Elnashar, J. Spencer-Smith, D. C. Schmidt, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2302.11382.
G. Wang, Y. Xie, Y. Jiang, A. Mandlekar, C. Xiao, Y. Zhu, L. Fan, A. Anandkumar, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2305.16291;
J. Liu, D. Shen, Y. Zhang, B. Dolan, L. Carin, W. Chen, arXiv preprint 2021, https://doi.org/10.48550/arXiv.2101.06804;
J. S. Park, J. C. O′Brien, C. J. Cai, M. R. Morris, P. Liang, M. S. Bernstein, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2304.03442;
W. Zhou, Y. E. Jiang, P. Cui, T. Wang, Z. Xiao, Y. Hou, R. Cotterell, M. Sachan, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2305.13304.
X. Pei, H.-B. Bürgi, E. A. Kapustin, Y. Liu, O. M. Yaghi, J. Am. Chem. Soc. 2019, 141, 18862-18869.
D. Saha, R. Zacharia, L. Lafi, D. Cossement, R. Chahine, Chem. Eng. J. 2011, 171, 517-525;
Y. Song, M. Yang, X. Zhang, Sep. Sci. Technol. 2022, 57, 1521-1534;
F. Gándara, H. Furukawa, S. Lee, O. M. Yaghi, J. Am. Chem. Soc. 2014, 136, 5271-5274.
Deposition numbers 2288419 (for MOF-521-H), 2288420 (for MOF-521-oF), and 2288418 (for MOF-521-mF) contain the supplementary crystallographic data for this paper. These data are provided free of charge by the joint Cambridge Crystallographic Data Centre and Fachinformationszentrum Karlsruhe Access Structures service.
S. Lee, E. A. Kapustin, O. M. Yaghi, Science 2016, 353, 808-811.
D. J. Tranchemontagne, J. L. Mendoza-Cortés, M. O'keeffe, O. M. Yaghi, Chem. Soc. Rev. 2009, 38, 1257-1283.
F. M. A. Noa, M. Abrahamsson, E. Ahlberg, O. Cheung, C. R. Göb, C. J. McKenzie, L. Öhrström, Chem 2021, 7, 2491-2512;
L. S. Xie, E. V. Alexandrov, G. Skorupskii, D. M. Proserpio, M. Dincă, Chem. Sci. 2019, 10, 8558-8565;
A. Schoedel, M. Li, D. Li, M. O'Keeffe, O. M. Yaghi, Chem. Rev. 2016, 116, 12466-12535.
M. O'Keeffe, M. A. Peskov, S. J. Ramsden, O. M. Yaghi, Acc. Chem. Res. 2008, 41, 1782-1789.
T. Düren, F. Millange, G. Férey, K. S. Walton, R. Q. Snurr, J. Phys. Chem. C 2007, 111, 15350-15356.
Y. Luo, S. Bag, O. Zaremba, A. Cierpka, J. Andreo, S. Wuttke, P. Friederich, M. Tsotsalas, Angew. Chem. Int. Ed. 2022, 61, e202200242;
S. Park, B. Kim, S. Choi, P. G. Boyd, B. Smit, J. Kim, J. Chem. Inf. Model. 2018, 58, 244-251;
A. Nandy, C. Duan, H. J. Kulik, J. Am. Chem. Soc. 2021, 143, 17535-17547;
H. Park, Y. Kang, W. Choe, J. Kim, J. Chem. Inf. Model. 2022, 62, 1190-1198.
D. A. Boiko, R. MacKnight, G. Gomes, arXiv preprint 2023, https://doi.org/10.48550/arXiv.2304.05332.