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Creators/Authors contains: "Kim, Seonah"

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  1. ; ; ; ; ; ; (, Digital Discovery)
    Using a MixSolDB, a curated solubility dataset for multicomponent solvent systems, a GNN-based framework with semi-supervised distillation from COSMO-RS data improved prediction accuracy and broadened applicability. 
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    Free, publicly-accessible full text available June 11, 2026
  2. ; ; ; ; ; (, Digital Discovery)
    In this work, we report the development of multiple new machine learning (ML) models to accurately predict homopolymer/copolymer solubility over a diverse set of polymers & solvents, using explainable AI to provide polymer design recommendations. 
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    Free, publicly-accessible full text available February 12, 2026
  3. ; ; ; ; ; ; ; ; ; ; et al (, ACS Catalysis)
    Free, publicly-accessible full text available May 16, 2026
  4. ; ; ; ; ; ; ; ; (, Fuel)
    Full Text Available 
  5. ; ; ; ; (, Chemical Science)
    Copsey, May; Apps, Samantha; Moore, James; Cotton, Carri; Huang, Tinge; Johnston, Esther; Orchar, Sophie; Thompson, Richard; Welch, Amy; Gough, Roger (Ed.)
    Our self-evolving graph neural networks for predicting solubilities reconciled different magnitudes of errors and uncertainties of experimental and computational databases, maximizing the database size and the model’s prediction accuracy. 
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    Full Text Available 
  6. ; ; ; ; ; ; (, Proceedings of the Combustion Institute)
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  7. ; ; ; ; ; ; ; ; (, Proceedings of the Combustion Institute)
    Full Text Available 
  8. ; ; ; ; (, Digital Discovery)
    Bond dissociation energetics underpin the thermodynamics of chemical transformations where bonds are broken or formed and can also be used to predict reaction rates and selectivities. 
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    Full Text Available 
  9. ; ; ; ; ; ; ; ; ; ; et al (, Sustainable Energy & Fuels)
    Quantitative sooting tendencies were measured for 10 lactones with a wide range of molecular structures. Lactones have potential as low-soot, sugar-derived alternative fuels. 
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    Full Text Available 
  10. ; ; ; ; (, figshare)
    This dataset contains bond dissociation energies for 65540 molecules which represent a set of 531244 unique BDEs (enthalpies and free energies). This dataset is broken down into molecule, bond index, fragments and BDEs. 
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