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solubility

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A machine learning pipeline for the prediction of aqueous solubility of small chemical compounds is proposed. Pairs of SMILES chemical structures and experimental values of the solubility are used to learn a model. A Flask application reads the SMILES chemical structure of a new compound and predicts the solubility missing value in logS units.

  • Updated Nov 28, 2020
  • Jupyter Notebook

Part of my work realized during the years as a PhD student. I was in the team MEMO of the CIRIMAT lab in Toulouse. I study via a multi-scale approach the influence influence of H, C, N impurities and point defects on the solubility and diffusion of the oxygen in the nickel (fcc phase). My works was under the supervision of Damien Connétable and …

  • Updated Dec 30, 2021

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