Tag: cheminformatics

Designing solvent systems in chemical processes using self-evolving solubility databases and graph neural networks. Yeonjoon Kim, Hojin Jung, Sabari Kumar, Alex Claiborne, Robert S. Paton, Seonah Kim. ChemRxiv preprint. DOI: 10.26434/chemrxiv-2022-sq34x.

Physics-informed graph neural networks for predicting cetane number with systematic data quality analysis Yeonjoon Kim, Jaeyoung Cho, Nimal Naser, Sabari Kumar, Keunhong Jeong, Robert L. McCormick, Peter C. St. John, Seonah Kim, Proc. Comb. Inst. (accepted 2022) DOI: 10.1016/j.proci.2022.09.059

A perspective on biomass-derived biofuels: from catalyst design principles to fuel properties, Yeonjoon Kim, Anna E. Thomas, David J. Robichaud, Kristiina Iisa, Peter C. St. John, Brian D. Etz, Gina M. Fioroni, Abhijit Dutta, Robert L. McCormick, Calvin Mukarakate, Seonah Kim, J. Haz. Mat., 400, 5, 123198 (2020).

Prediction of gas-phase homolytic bond dissociation energies at near chemical accuracy with sub-second computational cost, Peter C. St. John, Yanfei Guan, Yeonjoon Kim, Seonah Kim, Robert S. Paton, 10.26434/chemrxiv.10052048 (2019) and Nature Comm., 11, 2328 (2020).

Quantum chemical calculations for over 200,000 organic radical species and 40,000 associated closed-shell molecules, Peter St. John, Yanfei Guan, Yeonjoon Kim, Brian D. Etz, Seonah Kim, Robert S. Paton, Scientific Data, 7, 244 (2020).