ChemMiner: A Large Language Model Agent System for Chemical Literature Data Mining

Built on

M. C. Swain and J. M. Cole, “Chemdataextractor: a toolkit for automated extraction of chemical information from the scientific literature,” Journal of chemical information and modeling , vol. 56, no. 10, pp. 1894–1904, 2016
2016
Earlier work this paper cites.
D. T. Ahneman, J. G. Estrada, S. Lin, S. D. Dreher, and A. G. Doyle, “Predicting reaction performance in c–n cross-coupling using machine learning,” Science , vol. 360, no. 6385, pp. 186–190, 2018
2018
Earlier work this paper cites.
D. Perera, J. W. Tucker, S. Brahmbhatt, C. J. Helal, A. Chong, W. Farrell, P. Richardson, and N. W. Sach, “A platform for automated nanomole-scale reaction screening and micromole-scale synthesis in flow,” Science , vol. 359, no. 6374, pp. 429–434, 2018
2018
Earlier work this paper cites.
J. Guo, A. S. Ibanez-Lopez, H. Gao, V. Quach, C. W. Coley, K. F. Jensen, and R. Barzilay, “Automated chemical reaction extraction from scientific literature,” Journal of chemical information and modeling , vol. 62, no. 9, pp. 2035–2045, 2021
2021
Earlier work this paper cites.

J. Schleinitz, M. Langevin, Y. Smail, B. Wehnert, L. Grimaud, and R. Vuilleumier, “Machine learning yield prediction from nicolit, a small-size literature data set of nickel catalyzed c–o couplings,” Journal of the American Chemical Society , vol. 144, no. 32, pp. 14 722–14 730, 2022
2022
Cited alongside, same era.
K. Chen, G. Chen, J. Li, Y. Huang, E. Wang, T. Hou, and P.-A. Heng, “MetaRF: attention-based random forest for reaction yield prediction with a few trails,” Journal of Cheminformatics , vol. 15, no. 1, pp. 1–12, 2023
2023
Cited alongside, same era.
K. Chen, J. Li, K. Wang, Y. Du, J. Yu, J. Lu, G. Chen, L. Li, J. Qiu, Q. Fang et al. , “Towards an automatic ai agent for reaction condition recommendation in chemical synthesis,” arXiv preprint arXiv:2311.10776 , 2023
Original
2023
Cited alongside, same era.