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Award ID contains: 2304658

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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. ; ; ; ; (, 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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